{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "executionInfo": {
     "elapsed": 17502,
     "status": "ok",
     "timestamp": 1616745658761,
     "user": {
      "displayName": "Apurva Bhargava",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi3hHA-32IVQPOzXK40Itcc5oZmMDf0Vsnw_e_afg=s64",
      "userId": "07288249218888651888"
     },
     "user_tz": 240
    },
    "id": "XpXNw0djKJSI"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "importing Jupyter notebook from SelectIndices.ipynb\n",
      "E:\\Dropbox\\Optimal Training Sets\\Replication File v4\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import random\n",
    "import math\n",
    "from sklearn.model_selection import train_test_split\n",
    "import os\n",
    "\n",
    "import import_ipynb\n",
    "import SelectIndices as si\n",
    "\n",
    "# Set the random seed\n",
    "random.seed(10012)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "executionInfo": {
     "elapsed": 13431,
     "status": "ok",
     "timestamp": 1616745670957,
     "user": {
      "displayName": "Apurva Bhargava",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi3hHA-32IVQPOzXK40Itcc5oZmMDf0Vsnw_e_afg=s64",
      "userId": "07288249218888651888"
     },
     "user_tz": 240
    },
    "id": "ZBiPUkQLVFCg"
   },
   "outputs": [],
   "source": [
    "## Set up the simulation scope\n",
    "dataset_names = ['eo', 'stwts'] # ['eo', 'news', 'stwts']\n",
    "embed_types = ['cvec_pca16', 'cvec_nmf16', 'cvec_umap16', 'cvec_tsne16', 'bert', 'roberta', 'distil', 'glove6B', 'universal', 'lda100']\n",
    "counts = [50, 100, 250, 500, 750, 1000, 1500, 2000, 2500, 3000]\n",
    "#bootstrap_iters = [1,2]\n",
    "bootstrap_iters = [1,2,3,4,5,6,7,8,9,10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Set Difference helper\n",
    "def Diff(li1, li2):\n",
    "    return list(set(li1) - set(li2)) + list(set(li2) - set(li1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10218\n",
      "2044\n",
      "6264\n",
      "1253\n"
     ]
    }
   ],
   "source": [
    "## Read in the data\n",
    "eos_full = pd.read_csv(\"data/raw/\" + 'eo_clean_full.csv', index_col=0)\n",
    "max_obs_eo = len(eos_full)\n",
    "print(max_obs_eo)\n",
    "eo_test_set_size = math.ceil(max_obs_eo*0.2)\n",
    "print(eo_test_set_size)\n",
    "\n",
    "stwts_full = pd.read_csv(\"data/raw/\" +'stwts_clean_full.csv', index_col=0)\n",
    "max_obs_stwts = len(stwts_full)\n",
    "print(max_obs_stwts)\n",
    "stwts_test_set_size = math.ceil(max_obs_stwts*0.2)\n",
    "print(stwts_test_set_size)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Select train/test obs for each of the bootstrap iters\n",
    "\n",
    "eo_testset_list = []\n",
    "for i in range(len(bootstrap_iters)):\n",
    "    random.seed(i)\n",
    "    eo_testset_list.append(random.sample(range(0,max_obs_eo), eo_test_set_size))\n",
    "\n",
    "\n",
    "stwts_testset_list = []\n",
    "for i in range(len(bootstrap_iters)):\n",
    "    random.seed(i)\n",
    "    stwts_testset_list.append(random.sample(range(0,max_obs_stwts), stwts_test_set_size))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Output the lists of train/test obs\n",
    "\n",
    "eo_df = pd.DataFrame(eo_testset_list)\n",
    "eo_df = eo_df.transpose()\n",
    "eo_df.columns = [\"iter\" + str(x) for x in [1,2,3,4,5,6,7,8,9,10]]\n",
    "eo_df.to_csv(\"data/output/eo_testset_list.csv\", index = False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "stwts_df = pd.DataFrame(stwts_testset_list)\n",
    "stwts_df = stwts_df.transpose()\n",
    "stwts_df.columns = [\"iter\" + str(x) for x in [1,2,3,4,5,6,7,8,9,10]]\n",
    "\n",
    "os.getcwd()\n",
    "stwts_df.to_csv(\"data/output/stwts_testset_list.csv\", index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "10\n"
     ]
    }
   ],
   "source": [
    "print(len(eo_testset_list))\n",
    "print(len(stwts_testset_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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5479, 2627, 7677, 8639, 9033, 6741, 8128, 3146, 2744, 6404, 772, 5553, 8355, 5374, 3001, 7111, 2492, 8084, 3495, 7231, 539, 3980, 7991, 5204, 3217, 8, 713, 9727, 8677, 9584, 7261, 8921, 10154, 6971, 4692, 5540, 8342, 3148, 2674, 6105, 9675, 7178, 6403, 7190, 5202, 8765, 1103, 2401, 3600, 1856, 2552, 8577, 7600, 3440, 6027, 763, 348, 6654, 3396, 8367, 6755, 9371, 3448, 67, 2234, 8023, 5056, 6228, 1082, 1282, 8073, 9767, 3341, 6870, 5898, 5113, 1371, 380, 3917, 456, 8523, 2512, 7630, 4233, 1805, 7326, 4562, 3596, 6270, 9185, 5566, 8996, 4323, 1457, 721, 2536, 5169, 7946, 1037, 7855, 7122, 5233, 6316, 397, 1910, 7114, 2188, 2322, 509, 9819, 7041, 4061, 520, 4456, 4328, 6296, 1891, 5633, 4778, 6123, 3105, 976, 5550, 228, 8708, 8117, 359, 4224, 5432, 2255, 8493, 1627, 6842, 1108, 4120, 1707, 1230, 2101, 7950, 567, 3660, 5690, 1586, 3554, 2903, 3770, 6537, 3299, 7192, 5708, 2588, 4410, 5710, 3289, 3540, 8277, 5140, 2104, 4535, 7, 1364, 8949, 5052, 5296, 575, 9563, 231, 4790, 1878, 1363, 5831, 8230, 8020, 10189, 4200, 4543, 2837, 7086, 3678, 728, 8301, 4118, 4357, 6811, 3351, 1005]\n",
      "2044\n",
      "[2201, 9325, 1033, 4179, 1931, 8117, 7364, 7737, 6219, 3439, 1537, 7993, 464, 6386, 7090, 9952, 34, 7297, 4363, 3748, 9685, 1674, 5200, 501, 365, 416, 8870, 150, 6245, 3548, 6915, 475, 8644, 3632, 7174, 8123, 9058, 3818, 5663, 3782, 3584, 7530, 4747, 352, 6818, 9116, 1638, 3045, 4856, 1980, 5450, 8205, 10187, 8318, 3110, 4970, 4655, 9626, 8181, 8278, 6444, 9650, 565, 7868, 3977, 6623, 6788, 2834, 6014, 8991, 6139, 1416, 7191, 8330, 1768, 2682, 8535, 6443, 6070, 8023, 484, 7689, 712, 5054, 10073, 9718, 9472, 6448, 2791, 2762, 8228, 3718, 201, 3268, 8841, 8983, 3803, 6626, 8417, 5633, 9466, 5788, 7522, 4411, 8978, 9976, 93, 6286, 8396, 2117, 8498, 9197, 3366, 6981, 919, 7882, 5975, 9338, 9083, 3274, 8269, 6773, 7945, 5845, 6789, 5670, 25, 8822, 8849, 10034, 5425, 7506, 9828, 458, 3761, 2903, 9023, 9575, 2961, 1500, 9028, 4182, 531, 1154, 1363, 273, 7421, 238, 4607, 4088, 4401, 1793, 3024, 5643, 4756, 1138, 2743, 2615, 4181, 8640, 2754, 4471, 4824, 7449, 5275, 8134, 7762, 1870, 387, 5111, 6333, 5625, 6896, 3080, 4233, 1781, 4152, 8357, 3425, 9922, 7072, 341, 3692, 292, 6509, 2399, 578, 2625, 7301, 8295, 6990, 8924, 3614, 8463, 7386, 3656, 8583, 502, 6470, 9434, 5263, 6984, 963, 4892, 2059, 3475, 777, 5019, 1158, 1252, 5084, 4880, 2592, 10173, 9255, 4134, 2136, 138, 9186, 621, 9676, 3565, 9343, 7550, 2810, 8337, 613, 6192, 3283, 5684, 1622, 3371, 9394, 7093, 9689, 3180, 8066, 1710, 6390, 4850, 8259, 8188, 281, 5330, 6591, 4609, 296, 2571, 3290, 5369, 9229, 2214, 5555, 7032, 3490, 4366, 1579, 6213, 8972, 10118, 8754, 7938, 8724, 3844, 1070, 661, 1387, 2179, 2780, 2728, 8818, 3489, 4391, 5443, 9833, 8288, 10076, 6031, 5551, 5575, 1866, 4771, 3853, 9895, 8008, 2217, 9502, 9030, 1708, 5254, 641, 6661, 1199, 6229, 2413, 2048, 5585, 1879, 9624, 6193, 1255, 9351, 9015, 3665, 9272, 1339, 4370, 5978, 4842, 9247, 8753, 1872, 7500, 4541, 1765, 749, 4845, 202, 10070, 1502, 6775, 1885, 655, 3078, 3926, 9614, 6897, 2654, 1893, 7387, 2742, 3955, 2604, 1684, 7128, 6197, 8895, 4817, 9014, 4151, 7815, 5152, 1640, 3401, 10195, 649, 446, 172, 9909, 9774, 5246, 7370, 6410, 5132, 6529, 1031, 1051, 5199, 9854, 7468, 1824, 4097, 3525, 9881, 7682, 5829, 4244, 3001, 8873, 3405, 5035, 3263, 4036, 5905, 1333, 4600, 1464, 7338, 1482, 9410, 5552, 3726, 6397, 5026, 672, 5361, 3060, 5189, 9486, 4961, 4027, 5477, 1653, 8916, 9829, 9764, 1508, 4015, 3607, 333, 3993, 6582, 1185, 9945, 9930, 1161, 1230, 10174, 162, 4764, 5884, 8081, 7681, 2526, 9825, 8215, 5375, 1263, 8343, 2838, 2942, 2450, 2318, 5239, 5007, 1751, 8427, 4808, 2069, 3387, 2321, 8937, 520, 5178, 9059, 3365, 2918, 4897, 7088, 8806, 2586, 795, 4051, 4138, 1055, 7318, 7047, 8999, 4099, 8869, 7199, 8815, 7427, 178, 6483, 5548, 9993, 4226, 7959, 399, 6826, 9348, 309, 1021, 5815, 9503, 2265, 9724, 2050, 2269, 4245, 4536, 6517, 9241, 6571, 2820, 1462, 3826, 7962, 122, 2909, 8662, 5197, 8206, 7181, 3698, 3905, 5127, 8111, 7845, 3687, 6754, 5520, 9181, 4509, 3595, 789, 1172, 8383, 6040, 2612, 8382, 3339, 5108, 4894, 4908, 9049, 6088, 2706, 7614, 1392, 2019, 8420, 9359, 6180, 2888, 2552, 4105, 6991, 9996, 9330, 854, 8110, 10130, 5701, 6291, 8438, 2700, 9824, 666, 8588, 1481, 4180, 1655, 4383, 1371, 2279, 1343, 7291, 3948, 6264, 7092, 6508, 2699, 5332, 7178, 9789, 7994, 3473, 1952, 7065, 8749, 6688, 1934, 4841, 4549, 4066, 6207, 9164, 65, 10163, 8656, 7188, 9487, 344, 504, 3968, 4266, 3385, 2832, 4665, 2431, 8885, 3284, 4476, 5097, 9596, 4110, 7313, 2752, 8935, 5848, 8041, 6880, 1995, 3423, 9347, 6279, 3355, 4653, 1771, 395, 9664, 9327, 216, 8933, 10169, 2237, 1231, 8198, 6123, 9381, 5099, 7162, 8241, 5846, 8657, 5303, 13, 2029, 7246, 7365, 5737, 4993, 8835, 6543, 5560, 9362, 8065, 1852, 6185, 6265, 3340, 9124, 63, 4548, 8371, 3258, 7562, 8469, 6700, 5002, 2790, 7362, 8699, 3233, 5888, 8621, 57, 6376, 9492, 6977, 6639, 5505, 1109, 8072, 4057, 4765, 340, 6668, 2557, 10033, 4427, 9781, 1202, 165, 5725, 4334, 6736, 9983, 4975, 2491, 7570, 4249, 9956, 2779, 7653, 8361, 743, 4437, 8360, 1615, 6923, 1142, 5819, 1097, 7249, 323, 2689, 8309, 2648, 1524, 6585, 4518, 4987, 3422, 8652, 3403, 3886, 5471, 4408, 1123, 1226, 8572, 6032, 7666, 8380, 9136, 814, 2761, 4864, 9113, 4419, 5830, 3802, 6431, 9192, 6548, 2823, 7923, 4252, 5400, 3642, 4239, 4001, 500, 6596, 5186, 7074, 4070, 9527, 3111, 1188, 2713, 9488, 7267, 2427, 4292, 7526, 8627, 2662, 2271, 2262, 7220, 5916, 5075, 6565, 3940, 1897, 3378, 5005, 1117, 1743, 3729, 6504, 5265, 9981, 1637, 3059, 736, 906, 381, 10188, 568, 8101, 8659, 9607, 5610, 4498, 9625, 2829, 1560, 3638, 9510, 3821, 9695, 7369, 6191, 10128, 3796, 3862, 4647, 7578, 8962, 6383, 3471, 7400, 4225, 5408, 8131, 1817, 3503, 1291, 757, 252, 85, 7870, 5235, 6277, 4705, 3209, 6552, 2622, 2494, 499, 248, 6345, 2378, 8889, 935, 9252, 6217, 4164, 2129, 1302, 7583, 10162, 236, 581, 8797, 996, 8600, 2112, 701, 4482, 1924, 7086, 1491, 3114, 452, 8186, 2135, 4575, 3144, 7332, 6384, 5403, 4390, 4257, 3982, 4021, 986, 2871, 5728, 7020, 9179, 8555, 9407, 5787, 8960, 6760, 8816, 3266, 8788, 6948, 1148, 4376, 1184, 4121, 9737, 1582, 2474, 961, 3331, 7014, 735, 865, 1494, 8402, 7686, 8210, 6066, 1626, 5123, 657, 2074, 8707, 543, 7263, 2100, 6474, 7308, 403, 8593, 4423, 1480, 4096, 5331, 1405, 4945, 560, 6295, 952, 4276, 5131, 2130, 4264, 6228, 1919, 4976, 1541, 6960, 4020, 8236, 9128, 9782, 9439, 9762, 8344, 6407, 7883, 1715, 2125, 7350, 8581, 9152, 8520, 8775, 495, 4773, 2572, 3276, 6067, 6377, 8537, 5312, 1595, 6709, 5658, 2070, 1062, 713, 4923, 8743, 5138, 6841, 4887, 5223, 5777, 4467, 5329, 8521, 8209, 141, 8620, 1996, 2437, 5195, 5334, 5366, 1127, 7402, 4581, 7859, 7440, 5966, 6234, 1280, 10103, 2204, 798, 8580, 8063, 4127, 10216, 9320, 5924, 6064, 6595, 5036, 7611, 5577, 8718, 8315, 2749, 476, 2430, 4098, 3623, 9220, 2185, 1847, 10065, 6735, 820, 1625, 8940, 4353, 1752, 3347, 4287, 1094, 8624, 1286, 1192, 3561, 2840, 9521, 7079, 357, 9940, 7973, 4648, 3603, 9989, 8087, 9935, 6970, 7408, 6015, 8920, 3093, 7899, 1191, 4203, 6673, 3299, 135, 8716, 6237, 8426, 7980, 1251, 6614, 8356, 6972, 9353, 5764, 7511, 104, 3109, 4904, 90, 8860, 1966, 4958, 10109, 5170, 8896, 9033, 4628, 8611, 6740, 8880, 8484, 6689, 5042, 7414, 4946, 2145, 10028, 7277, 2299, 9011, 2670, 4140, 157, 6949, 593, 6035, 6895, 6588, 4612, 300, 9839, 1475, 78, 6281, 4405, 7608, 4455, 6105, 7887, 5513, 6364, 7473, 1908, 7925, 5808, 2370, 6802, 2429, 297, 2819, 4263, 6025, 2082, 4704, 6765, 9440, 10119, 4706, 6893, 4483, 7102, 5503, 9759, 3530, 8050, 6584, 6965, 1497, 9773, 2121, 3377, 2451, 3755, 428, 1691, 4148, 2551, 7860, 1621, 6539, 3070, 49, 1460, 7007, 833, 9004, 3576, 8757, 6912, 5680, 770, 1690, 9057, 6875, 1943, 4347, 4567, 2933, 9274, 781, 3509, 1428, 6385, 2028, 7328, 4820, 8320, 8158, 6440, 1903, 7851, 1733, 2443, 6330, 3296, 2738, 8531, 4220, 6825, 8793, 4728, 8068, 8925, 3516, 5522, 9739, 1685, 140, 5683, 9683, 924, 8856, 7213, 4912, 1650, 3744, 8323, 9459, 4429, 9845, 6744, 9251, 2133, 4199, 3199, 6680, 957, 8729, 8345, 2438, 6779, 4426, 4584, 7866, 5010, 4375, 8049, 3512, 8171, 6024, 7709, 3959, 5544, 2886, 2968, 7391, 8761, 2448, 9335, 8256, 5341, 8658, 2212, 3492, 5166, 8089, 9431, 5407, 1939, 2095, 2295, 4201, 3686, 1442, 8828, 819, 9144, 1902, 3706, 3267, 9613, 5044, 6918, 5368, 69, 328, 9586, 3608, 1385, 3678, 4590, 5588, 9497, 8493, 6214, 378, 1993, 5404, 5685, 2284, 1857, 4109, 2347, 9943, 8985, 1267, 1504, 9102, 4914, 5194, 4078, 4412, 8677, 815, 5927, 510, 1283, 2277, 6542, 6095, 3965, 10207, 5387, 9134, 130, 8441, 5272, 1838, 5773, 2062, 4441, 6638, 1492, 8646, 7791, 6860, 8777, 6451, 4933, 3594, 9511, 2181, 883, 8331, 1800, 2869, 3941, 3522, 7120, 4497, 327, 4102, 9009, 4438, 8685, 4288, 7753, 2065, 6607, 1699, 6119, 1131, 9558, 5949, 8312, 498, 5048, 7298, 2166, 9701, 1218, 2325, 3543, 7931, 5496, 5981, 4789, 2617, 2549, 6254, 7204, 6646, 10213, 9420, 9515, 4838, 134, 8802, 158, 2172, 9416, 1657, 7528, 497, 7077, 9001, 4523, 9260, 6691, 6654, 7569, 872, 9242, 7712, 612, 9, 689, 1820, 2286, 8690, 8324, 5837, 8930, 5839, 7764, 4016, 3929, 1729, 5860, 2599, 1907, 664, 5139, 6920, 5673, 4153, 912, 7124, 6798, 6165, 5877, 4815, 5590, 7225, 3900, 8503, 2365, 918, 5595, 1859, 8405, 2821, 7986, 5586, 1990, 354, 10154, 3427, 6278, 2862, 9675, 3732, 1633, 4069, 5498, 5391, 8868, 7558, 7719, 6054, 8071, 3174, 9419, 7218, 6534, 1972, 7999, 4365, 2051, 2455, 195, 6162, 6793, 1785, 429, 1222, 2997, 7516, 6177, 8225, 4726, 2547, 2527, 8595, 1732, 4171, 307, 7609, 6497, 3741, 6402, 87, 4087, 6929, 2603, 9096, 5611, 3918, 1246, 2636, 2877, 6155, 353, 8406, 3553, 7002, 3861, 662, 8448, 3116, 8258, 1265, 4061, 6523, 7617, 1951, 792, 6340, 1469, 1549, 7846, 9468, 8494, 8786, 199, 10036, 10048, 7641, 4555, 6808, 2731, 2182, 5215, 7351, 8218, 6842, 2746, 6479, 6374, 3288, 8116, 4561, 5898, 2481, 4250, 4579, 8938, 1370, 5906, 5506, 2338, 4234, 4178, 4133, 5723, 9336, 4573, 7663, 220, 2441, 2134, 9172, 3701, 3219, 10074, 3250, 9964, 8867, 2280, 7544, 6411, 3208, 1352, 1264, 2508, 942, 9309, 6641, 6268, 6836, 2252, 2116, 1215, 3952, 6253, 8984, 4680, 3316, 6507, 9612, 2921, 3688, 4879, 2356, 5697, 8062, 4780, 1451, 9207, 9780, 3421, 7593, 358, 10063, 1688, 9156, 9577, 4176, 954, 853, 9190, 2619, 2168, 1692, 1843, 7131, 4028, 9848, 8261, 10164, 6501, 1991, 3476, 6288, 8477, 2194, 8798, 59, 10168, 3302, 9918, 7897, 3779, 4385, 617, 2748, 8238, 3819, 6724, 4484, 6900, 9863, 4456, 8093, 1601, 2123, 3058, 260, 7437, 734, 8002, 3511, 6454, 5509, 3989, 1540, 9800, 698, 6924, 7238, 9216, 9798, 8224, 3112, 8351, 6304, 8549, 5907, 3228, 3812, 5893, 1056, 5587, 848, 9199, 724, 2896, 2419, 4678, 9358, 705, 9285, 9297, 6492, 1507, 9426, 8384, 4936, 6461, 4389, 5770, 7710, 804, 7817, 285, 6993, 4990, 5198, 2447, 4551, 1079, 5914, 6801, 6406, 8516, 10049, 8844, 605, 235, 9803, 5440, 5516, 6034, 564, 8886, 8701, 10095, 1372, 7310, 5480, 8193, 55, 2633, 5325, 5912, 3505, 2394, 2428, 1767, 6618, 9735, 8333, 9167, 8741, 5593, 4256, 6037, 616, 1039, 4041, 4350, 6505, 4650, 1367, 1227, 10129, 4379, 9043, 1364, 2068, 4627, 4305, 3847, 3450, 1619, 4540, 7871, 771, 8391, 8596, 9595, 9811, 5168, 5565, 9978, 8456, 2183, 577, 7245, 5962, 610, 470, 9286, 6840, 2683, 665, 6956, 3020, 3234, 3814, 1880, 9332, 8294, 2006, 4367, 7509, 3216, 905, 5919, 9312, 5487, 5811, 3600, 153, 228, 8007, 528, 2693, 4150, 653, 10190, 3769, 1386, 2839, 575, 3280, 3431, 7257, 4731, 3981, 8036, 9942, 6084, 5323, 6422, 1203, 3198, 2973, 3072, 4865, 6983, 7766, 5955, 379, 7984, 338, 1716, 7085, 5629, 9837, 1213, 6884, 9711, 8425, 8099, 8602, 7825, 7374, 8825, 2709, 4395, 4940, 6495, 9747, 4184, 5083, 240, 751, 7496, 8435, 5825, 10121, 8322, 9176, 3426, 7798, 8829, 2372, 6289, 7165, 888, 1822, 8872, 8897, 4191, 885, 5020, 6205, 245, 5316, 5540, 5059, 9519, 3417, 9912, 5384, 1964, 1085, 2103, 4821, 6711, 5583, 3810, 445, 2998, 8260, 5993, 4956, 4812, 8653, 6888, 7560, 8568, 3260, 6679, 3794, 691, 3944, 3679, 8629, 6466, 6215, 3443, 2490, 4902, 5899, 23, 5034, 7278, 8157, 2799, 2398, 8968, 6074, 7159, 5601, 10138, 5203, 1827, 4788, 8887, 7037, 185, 5090, 10146, 8059, 1883, 9357, 3613, 4336, 7156, 6106, 3777, 8423, 1679, 2671, 9315, 4785, 791, 1119, 3575, 51, 1012, 8790, 9653, 1084, 901, 146, 571, 5556, 5451, 9408, 144, 3462, 7683, 3278, 4362, 4839, 4118, 3825, 2992, 3452, 6413, 979, 3909, 7415, 579, 5429, 5352, 6664, 1961, 262, 3031, 8283, 1534, 3028, 3577, 3684, 2892, 4983, 1602, 10015, 5142, 2396, 1029, 7260, 2458, 3783, 706, 4689, 5641, 955, 9741, 7250, 8478, 8832, 3032, 9668, 941, 3315, 8418, 1899, 1432, 3601, 4687, 4130, 6927, 4073, 8487, 4124, 3191, 5337, 5733, 5852, 7442, 6266, 6332, 9841, 10104, 4005, 8017, 5631, 2926, 1865, 3927, 9370, 7153, 4537, 4977, 5489, 6071, 6705, 7476, 5969, 5765, 5175, 6488, 7722, 280, 9356, 2086, 4954, 9638, 4951, 2076, 2449, 2734, 7498, 9424, 9966, 2639, 1305, 4159, 3857, 5831, 5164, 9761, 4542, 7750, 5074, 8772, 7018, 2523, 9379, 7367, 1760, 8914, 5174, 1133, 9831, 7857, 572, 767, 3140, 5832, 5997, 5821, 6136, 5604, 9947, 3025, 6151, 534, 8871, 8381, 1022, 4046, 9533, 5358, 6602, 4003, 8613, 810, 1898, 7715, 2380, 5715, 4656, 8562, 1600, 9776, 10206, 9573, 9857, 3021, 4146, 7293, 8517, 1153, 1330]\n",
      "2044\n"
     ]
    }
   ],
   "source": [
    "print(eo_testset_list[0])\n",
    "print(len(eo_testset_list[0]))\n",
    "\n",
    "print(eo_testset_list[1])\n",
    "print(len(eo_testset_list[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Yn3HHCdprkjz"
   },
   "source": [
    "## Random pick"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 52
    },
    "executionInfo": {
     "elapsed": 1929,
     "status": "ok",
     "timestamp": 1616737793386,
     "user": {
      "displayName": "Apurva Bhargava",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi3hHA-32IVQPOzXK40Itcc5oZmMDf0Vsnw_e_afg=s64",
      "userId": "07288249218888651888"
     },
     "user_tz": 240
    },
    "id": "bHEiNOADD3R6",
    "outputId": "8c0cd288-27f2-46ac-8fbb-25cffd59abd8"
   },
   "outputs": [],
   "source": [
    "for i in range(len(eo_testset_list)):\n",
    "    indices_list = []\n",
    "    for c in counts:\n",
    "        remaining_obs = Diff(range(1, max_obs_eo), eo_testset_list[i])\n",
    "        indices_list.append(random.sample(remaining_obs, c))\n",
    "    with open(\"data/output/\" +'indices_eo_random_iter' + str(i+1) + '.txt', 'w') as filehandle:\n",
    "        filehandle.writelines(\"%s\\n\" % idl for idl in indices_list)\n",
    "\n",
    "for i in range(len(stwts_testset_list)):\n",
    "    indices_list = []\n",
    "    for c in counts:\n",
    "        remaining_obs = Diff(range(1, max_obs_stwts), stwts_testset_list[i])\n",
    "        indices_list.append(random.sample(remaining_obs, c))\n",
    "    with open(\"data/output/\" +'indices_stwts_random_iter' + str(i+1) + '.txt', 'w') as filehandle:\n",
    "        filehandle.writelines(\"%s\\n\" % idl for idl in indices_list)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gRB7M4YmD3lf"
   },
   "source": [
    "## K-means Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 481991,
     "status": "ok",
     "timestamp": 1616738304776,
     "user": {
      "displayName": "Apurva Bhargava",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi3hHA-32IVQPOzXK40Itcc5oZmMDf0Vsnw_e_afg=s64",
      "userId": "07288249218888651888"
     },
     "user_tz": 240
    },
    "id": "EU8Q2KwvrjpL",
    "outputId": "ee85c1f5-0484-4d55-cae7-c368e7e186e5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 62 iterations (1.147s) to cluster 8173 items into 50 clusters\n",
      "used 100 iterations (1.17s) to cluster 8173 items into 100 clusters\n",
      "used 45 iterations (1.244s) to cluster 8173 items into 250 clusters\n",
      "used 25 iterations (1.398s) to cluster 8173 items into 500 clusters\n",
      "used 21 iterations (1.505s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.269s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (2.015s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.801s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (2.172s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (2.329s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 47 iterations (0.337s) to cluster 8173 items into 50 clusters\n",
      "used 44 iterations (0.479s) to cluster 8173 items into 100 clusters\n",
      "used 42 iterations (0.901s) to cluster 8173 items into 250 clusters\n",
      "used 32 iterations (1.801s) to cluster 8173 items into 500 clusters\n",
      "used 19 iterations (1.413s) to cluster 8173 items into 750 clusters\n",
      "used 18 iterations (1.799s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (2.061s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.881s) to cluster 8173 items into 2000 clusters\n",
      "used 16 iterations (4.49s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (2.45s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 21 iterations (0.127s) to cluster 8173 items into 50 clusters\n",
      "used 32 iterations (0.314s) to cluster 8173 items into 100 clusters\n",
      "used 47 iterations (1.209s) to cluster 8173 items into 250 clusters\n",
      "used 24 iterations (1.224s) to cluster 8173 items into 500 clusters\n",
      "used 20 iterations (1.466s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.376s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (2.03s) to cluster 8173 items into 1500 clusters\n",
      "used 100 iterations (19.92s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (24.8141s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (29.7751s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 53 iterations (0.324s) to cluster 8173 items into 50 clusters\n",
      "used 32 iterations (0.305s) to cluster 8173 items into 100 clusters\n",
      "used 34 iterations (0.983s) to cluster 8173 items into 250 clusters\n",
      "used 26 iterations (1.31s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.218s) to cluster 8173 items into 750 clusters\n",
      "used 17 iterations (1.825s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.451s) to cluster 8173 items into 1500 clusters\n",
      "used 11 iterations (2.146s) to cluster 8173 items into 2000 clusters\n",
      "used 13 iterations (3.179s) to cluster 8173 items into 2500 clusters\n",
      "used 12 iterations (3.543s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 37 iterations (1.582s) to cluster 8173 items into 50 clusters\n",
      "used 38 iterations (1.789s) to cluster 8173 items into 100 clusters\n",
      "used 19 iterations (1.157s) to cluster 8173 items into 250 clusters\n",
      "used 21 iterations (2.019s) to cluster 8173 items into 500 clusters\n",
      "used 18 iterations (2.275s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.688s) to cluster 8173 items into 1000 clusters\n",
      "used 8 iterations (1.714s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (2.452s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.667s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (2.957s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 51 iterations (2.146s) to cluster 8173 items into 50 clusters\n",
      "used 25 iterations (1.168s) to cluster 8173 items into 100 clusters\n",
      "used 27 iterations (1.661s) to cluster 8173 items into 250 clusters\n",
      "used 16 iterations (1.531s) to cluster 8173 items into 500 clusters\n",
      "used 13 iterations (1.614s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (2.108s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (2.538s) to cluster 8173 items into 1500 clusters\n",
      "used 16 iterations (4.948s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.766s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (2.736s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (1.348s) to cluster 8173 items into 50 clusters\n",
      "used 36 iterations (1.687s) to cluster 8173 items into 100 clusters\n",
      "used 27 iterations (1.633s) to cluster 8173 items into 250 clusters\n",
      "used 14 iterations (1.34s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.861s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (2.292s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (2.43s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (2.292s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.524s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (3.676s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 55 iterations (1.034s) to cluster 8173 items into 50 clusters\n",
      "used 48 iterations (1.109s) to cluster 8173 items into 100 clusters\n",
      "used 32 iterations (1.146s) to cluster 8173 items into 250 clusters\n",
      "used 21 iterations (1.278s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (0.978s) to cluster 8173 items into 750 clusters\n",
      "used 16 iterations (1.498s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (1.884s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.482s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.401s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.421s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 33 iterations (0.998s) to cluster 8173 items into 50 clusters\n",
      "used 32 iterations (1.116s) to cluster 8173 items into 100 clusters\n",
      "used 22 iterations (1.026s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (1.208s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.562s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.574s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.861s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.859s) to cluster 8173 items into 2000 clusters\n",
      "used 6 iterations (1.953s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (2.368s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.324s) to cluster 8173 items into 50 clusters\n",
      "used 21 iterations (0.319s) to cluster 8173 items into 100 clusters\n",
      "used 35 iterations (0.92s) to cluster 8173 items into 250 clusters\n",
      "used 24 iterations (1.175s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (1.207s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (1.381s) to cluster 8173 items into 1000 clusters\n",
      "used 14 iterations (1.905s) to cluster 8173 items into 1500 clusters\n",
      "used 12 iterations (2.444s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.834s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (2.585s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 17 iterations (0.02s) to cluster 5012 items into 50 clusters\n",
      "used 28 iterations (0.185s) to cluster 5012 items into 100 clusters\n",
      "used 11 iterations (0.155s) to cluster 5012 items into 250 clusters\n",
      "used 15 iterations (0.38s) to cluster 5012 items into 500 clusters\n",
      "used 12 iterations (0.46s) to cluster 5012 items into 750 clusters\n",
      "used 11 iterations (0.773s) to cluster 5012 items into 1000 clusters\n",
      "used 10 iterations (0.766s) to cluster 5012 items into 1500 clusters\n",
      "used 6 iterations (0.79s) to cluster 5012 items into 2000 clusters\n",
      "used 5 iterations (0.842s) to cluster 5012 items into 2500 clusters\n",
      "used 7 iterations (1.378s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 17 iterations (0.02s) to cluster 5012 items into 50 clusters\n",
      "used 14 iterations (0.091s) to cluster 5012 items into 100 clusters\n",
      "used 22 iterations (0.303s) to cluster 5012 items into 250 clusters\n",
      "used 10 iterations (0.262s) to cluster 5012 items into 500 clusters\n",
      "used 11 iterations (0.631s) to cluster 5012 items into 750 clusters\n",
      "used 11 iterations (0.772s) to cluster 5012 items into 1000 clusters\n",
      "used 7 iterations (0.55s) to cluster 5012 items into 1500 clusters\n",
      "used 7 iterations (0.789s) to cluster 5012 items into 2000 clusters\n",
      "used 5 iterations (0.652s) to cluster 5012 items into 2500 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 5 iterations (0.998s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 47 iterations (0.058s) to cluster 5012 items into 50 clusters\n",
      "used 23 iterations (0.145s) to cluster 5012 items into 100 clusters\n",
      "used 17 iterations (0.443s) to cluster 5012 items into 250 clusters\n",
      "used 11 iterations (0.278s) to cluster 5012 items into 500 clusters\n",
      "used 11 iterations (0.423s) to cluster 5012 items into 750 clusters\n",
      "used 12 iterations (0.823s) to cluster 5012 items into 1000 clusters\n",
      "used 9 iterations (0.949s) to cluster 5012 items into 1500 clusters\n",
      "used 9 iterations (0.931s) to cluster 5012 items into 2000 clusters\n",
      "used 10 iterations (1.723s) to cluster 5012 items into 2500 clusters\n",
      "used 12 iterations (2.075s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.037s) to cluster 5012 items into 50 clusters\n",
      "used 35 iterations (0.22s) to cluster 5012 items into 100 clusters\n",
      "used 23 iterations (0.314s) to cluster 5012 items into 250 clusters\n",
      "used 16 iterations (0.422s) to cluster 5012 items into 500 clusters\n",
      "used 15 iterations (0.596s) to cluster 5012 items into 750 clusters\n",
      "used 9 iterations (0.681s) to cluster 5012 items into 1000 clusters\n",
      "used 8 iterations (0.818s) to cluster 5012 items into 1500 clusters\n",
      "used 7 iterations (0.725s) to cluster 5012 items into 2000 clusters\n",
      "used 13 iterations (1.969s) to cluster 5012 items into 2500 clusters\n",
      "used 8 iterations (1.408s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.653s) to cluster 5012 items into 50 clusters\n",
      "used 18 iterations (0.545s) to cluster 5012 items into 100 clusters\n",
      "used 16 iterations (0.647s) to cluster 5012 items into 250 clusters\n",
      "used 14 iterations (0.89s) to cluster 5012 items into 500 clusters\n",
      "used 13 iterations (1.094s) to cluster 5012 items into 750 clusters\n",
      "used 7 iterations (0.746s) to cluster 5012 items into 1000 clusters\n",
      "used 6 iterations (0.87s) to cluster 5012 items into 1500 clusters\n",
      "used 5 iterations (0.893s) to cluster 5012 items into 2000 clusters\n",
      "used 4 iterations (0.882s) to cluster 5012 items into 2500 clusters\n",
      "used 3 iterations (0.744s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.646s) to cluster 5012 items into 50 clusters\n",
      "used 22 iterations (0.653s) to cluster 5012 items into 100 clusters\n",
      "used 14 iterations (0.553s) to cluster 5012 items into 250 clusters\n",
      "used 10 iterations (0.639s) to cluster 5012 items into 500 clusters\n",
      "used 11 iterations (0.938s) to cluster 5012 items into 750 clusters\n",
      "used 9 iterations (0.939s) to cluster 5012 items into 1000 clusters\n",
      "used 6 iterations (0.867s) to cluster 5012 items into 1500 clusters\n",
      "used 5 iterations (0.911s) to cluster 5012 items into 2000 clusters\n",
      "used 4 iterations (0.88s) to cluster 5012 items into 2500 clusters\n",
      "used 3 iterations (0.759s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 54 iterations (1.277s) to cluster 5012 items into 50 clusters\n",
      "used 53 iterations (1.561s) to cluster 5012 items into 100 clusters\n",
      "used 17 iterations (0.674s) to cluster 5012 items into 250 clusters\n",
      "used 15 iterations (0.948s) to cluster 5012 items into 500 clusters\n",
      "used 10 iterations (0.86s) to cluster 5012 items into 750 clusters\n",
      "used 9 iterations (0.932s) to cluster 5012 items into 1000 clusters\n",
      "used 8 iterations (1.131s) to cluster 5012 items into 1500 clusters\n",
      "used 8 iterations (1.508s) to cluster 5012 items into 2000 clusters\n",
      "used 4 iterations (1.151s) to cluster 5012 items into 2500 clusters\n",
      "used 4 iterations (1.198s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 33 iterations (0.345s) to cluster 5012 items into 50 clusters\n",
      "used 22 iterations (0.348s) to cluster 5012 items into 100 clusters\n",
      "used 22 iterations (0.556s) to cluster 5012 items into 250 clusters\n",
      "used 24 iterations (0.95s) to cluster 5012 items into 500 clusters\n",
      "used 15 iterations (0.821s) to cluster 5012 items into 750 clusters\n",
      "used 17 iterations (1.722s) to cluster 5012 items into 1000 clusters\n",
      "used 9 iterations (1.19s) to cluster 5012 items into 1500 clusters\n",
      "used 10 iterations (1.586s) to cluster 5012 items into 2000 clusters\n",
      "used 7 iterations (1.408s) to cluster 5012 items into 2500 clusters\n",
      "used 10 iterations (2.441s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 16 iterations (0.269s) to cluster 5012 items into 50 clusters\n",
      "used 17 iterations (0.383s) to cluster 5012 items into 100 clusters\n",
      "used 15 iterations (0.486s) to cluster 5012 items into 250 clusters\n",
      "used 10 iterations (0.484s) to cluster 5012 items into 500 clusters\n",
      "used 11 iterations (0.836s) to cluster 5012 items into 750 clusters\n",
      "used 8 iterations (0.74s) to cluster 5012 items into 1000 clusters\n",
      "used 6 iterations (0.779s) to cluster 5012 items into 1500 clusters\n",
      "used 4 iterations (0.664s) to cluster 5012 items into 2000 clusters\n",
      "used 3 iterations (0.603s) to cluster 5012 items into 2500 clusters\n",
      "used 4 iterations (1.198s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 14 iterations (0.071s) to cluster 5012 items into 50 clusters\n",
      "used 17 iterations (0.179s) to cluster 5012 items into 100 clusters\n",
      "used 14 iterations (0.319s) to cluster 5012 items into 250 clusters\n",
      "used 11 iterations (0.325s) to cluster 5012 items into 500 clusters\n",
      "used 10 iterations (0.447s) to cluster 5012 items into 750 clusters\n",
      "used 9 iterations (0.57s) to cluster 5012 items into 1000 clusters\n",
      "used 7 iterations (0.615s) to cluster 5012 items into 1500 clusters\n",
      "used 8 iterations (1.367s) to cluster 5012 items into 2000 clusters\n",
      "used 5 iterations (0.817s) to cluster 5012 items into 2500 clusters\n",
      "used 5 iterations (1.63s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 64 iterations (0.383s) to cluster 8173 items into 50 clusters\n",
      "used 94 iterations (1.202s) to cluster 8173 items into 100 clusters\n",
      "used 34 iterations (0.971s) to cluster 8173 items into 250 clusters\n",
      "used 35 iterations (2.029s) to cluster 8173 items into 500 clusters\n",
      "used 23 iterations (2.344s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.599s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (2.425s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.929s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.27s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (2.756s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 55 iterations (0.316s) to cluster 8173 items into 50 clusters\n",
      "used 54 iterations (0.529s) to cluster 8173 items into 100 clusters\n",
      "used 48 iterations (1.249s) to cluster 8173 items into 250 clusters\n",
      "used 25 iterations (1.111s) to cluster 8173 items into 500 clusters\n",
      "used 31 iterations (2.552s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.847s) to cluster 8173 items into 1000 clusters\n",
      "used 15 iterations (2.603s) to cluster 8173 items into 1500 clusters\n",
      "used 12 iterations (4.071s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (4.577s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.515s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (0.18s) to cluster 8173 items into 50 clusters\n",
      "used 56 iterations (0.807s) to cluster 8173 items into 100 clusters\n",
      "used 37 iterations (1.216s) to cluster 8173 items into 250 clusters\n",
      "used 28 iterations (1.632s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (1.623s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (1.874s) to cluster 8173 items into 1000 clusters\n",
      "used 27 iterations (7.018s) to cluster 8173 items into 1500 clusters\n",
      "used 100 iterations (24.454s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (24.845s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (29.97s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.164s) to cluster 8173 items into 50 clusters\n",
      "used 39 iterations (0.381s) to cluster 8173 items into 100 clusters\n",
      "used 21 iterations (0.647s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (0.843s) to cluster 8173 items into 500 clusters\n",
      "used 18 iterations (1.419s) to cluster 8173 items into 750 clusters\n",
      "used 13 iterations (1.329s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.52s) to cluster 8173 items into 1500 clusters\n",
      "used 100 iterations (19.486s) to cluster 8173 items into 2000 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 100 iterations (24.211s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (29.738s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 51 iterations (2.245s) to cluster 8173 items into 50 clusters\n",
      "used 35 iterations (1.692s) to cluster 8173 items into 100 clusters\n",
      "used 18 iterations (1.158s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (2.147s) to cluster 8173 items into 500 clusters\n",
      "used 11 iterations (1.823s) to cluster 8173 items into 750 clusters\n",
      "used 13 iterations (2.486s) to cluster 8173 items into 1000 clusters\n",
      "used 12 iterations (3.117s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (2.647s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.606s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (3.665s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 40 iterations (1.736s) to cluster 8173 items into 50 clusters\n",
      "used 42 iterations (2.051s) to cluster 8173 items into 100 clusters\n",
      "used 31 iterations (2.06s) to cluster 8173 items into 250 clusters\n",
      "used 15 iterations (1.66s) to cluster 8173 items into 500 clusters\n",
      "used 16 iterations (2.444s) to cluster 8173 items into 750 clusters\n",
      "used 17 iterations (3.174s) to cluster 8173 items into 1000 clusters\n",
      "used 9 iterations (2.22s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (2.825s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.514s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (4.093s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 43 iterations (1.887s) to cluster 8173 items into 50 clusters\n",
      "used 41 iterations (1.95s) to cluster 8173 items into 100 clusters\n",
      "used 17 iterations (1.047s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (1.849s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (2.069s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (2.592s) to cluster 8173 items into 1000 clusters\n",
      "used 8 iterations (1.966s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (2.803s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.747s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (3.105s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.518s) to cluster 8173 items into 50 clusters\n",
      "used 41 iterations (0.989s) to cluster 8173 items into 100 clusters\n",
      "used 28 iterations (1.021s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (1.245s) to cluster 8173 items into 500 clusters\n",
      "used 16 iterations (1.556s) to cluster 8173 items into 750 clusters\n",
      "used 13 iterations (1.777s) to cluster 8173 items into 1000 clusters\n",
      "used 14 iterations (2.668s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (2.062s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.033s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.736s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (0.944s) to cluster 8173 items into 50 clusters\n",
      "used 27 iterations (0.936s) to cluster 8173 items into 100 clusters\n",
      "used 20 iterations (0.974s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (1.221s) to cluster 8173 items into 500 clusters\n",
      "used 16 iterations (1.907s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.955s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (2.359s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (2.029s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.397s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.759s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (0.32s) to cluster 8173 items into 50 clusters\n",
      "used 28 iterations (0.631s) to cluster 8173 items into 100 clusters\n",
      "used 26 iterations (0.714s) to cluster 8173 items into 250 clusters\n",
      "used 22 iterations (1.199s) to cluster 8173 items into 500 clusters\n",
      "used 18 iterations (1.602s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.219s) to cluster 8173 items into 1000 clusters\n",
      "used 12 iterations (1.941s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.971s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (2.507s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (2.543s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 20 iterations (0.028s) to cluster 5010 items into 50 clusters\n",
      "used 18 iterations (0.113s) to cluster 5010 items into 100 clusters\n",
      "used 13 iterations (0.179s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.567s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.455s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.768s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.7s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.926s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.988s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.962s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 12 iterations (0.014s) to cluster 5010 items into 50 clusters\n",
      "used 23 iterations (0.149s) to cluster 5010 items into 100 clusters\n",
      "used 15 iterations (0.2s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.518s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.458s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.423s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.661s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.614s) to cluster 5010 items into 2000 clusters\n",
      "used 7 iterations (1.103s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.962s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 17 iterations (0.023s) to cluster 5010 items into 50 clusters\n",
      "used 18 iterations (0.123s) to cluster 5010 items into 100 clusters\n",
      "used 18 iterations (0.252s) to cluster 5010 items into 250 clusters\n",
      "used 20 iterations (0.731s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (0.678s) to cluster 5010 items into 750 clusters\n",
      "used 15 iterations (0.767s) to cluster 5010 items into 1000 clusters\n",
      "used 12 iterations (1.154s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (1.134s) to cluster 5010 items into 2000 clusters\n",
      "used 12 iterations (1.955s) to cluster 5010 items into 2500 clusters\n",
      "used 8 iterations (1.428s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 15 iterations (0.021s) to cluster 5010 items into 50 clusters\n",
      "used 26 iterations (0.164s) to cluster 5010 items into 100 clusters\n",
      "used 22 iterations (0.516s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.402s) to cluster 5010 items into 500 clusters\n",
      "used 14 iterations (0.774s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.583s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.826s) to cluster 5010 items into 1500 clusters\n",
      "used 100 iterations (12.028s) to cluster 5010 items into 2000 clusters\n",
      "used 13 iterations (2.074s) to cluster 5010 items into 2500 clusters\n",
      "used 100 iterations (18.185s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 42 iterations (1.034s) to cluster 5010 items into 50 clusters\n",
      "used 21 iterations (0.631s) to cluster 5010 items into 100 clusters\n",
      "used 14 iterations (0.564s) to cluster 5010 items into 250 clusters\n",
      "used 10 iterations (0.63s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.768s) to cluster 5010 items into 750 clusters\n",
      "used 12 iterations (1.472s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (1.083s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (1.252s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (1.448s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (1.283s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.729s) to cluster 5010 items into 50 clusters\n",
      "used 22 iterations (0.665s) to cluster 5010 items into 100 clusters\n",
      "used 18 iterations (0.731s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.775s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (1.098s) to cluster 5010 items into 750 clusters\n",
      "used 7 iterations (0.943s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.873s) to cluster 5010 items into 1500 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 5 iterations (1.117s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (1.555s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (1.23s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 25 iterations (0.612s) to cluster 5010 items into 50 clusters\n",
      "used 33 iterations (0.999s) to cluster 5010 items into 100 clusters\n",
      "used 19 iterations (0.772s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.919s) to cluster 5010 items into 500 clusters\n",
      "used 17 iterations (1.676s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.953s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (1.235s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (1.286s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (1.307s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (1.472s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.294s) to cluster 5010 items into 50 clusters\n",
      "used 37 iterations (0.561s) to cluster 5010 items into 100 clusters\n",
      "used 28 iterations (0.669s) to cluster 5010 items into 250 clusters\n",
      "used 20 iterations (0.742s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.832s) to cluster 5010 items into 750 clusters\n",
      "used 12 iterations (1.006s) to cluster 5010 items into 1000 clusters\n",
      "used 12 iterations (1.478s) to cluster 5010 items into 1500 clusters\n",
      "used 13 iterations (2.2624s) to cluster 5010 items into 2000 clusters\n",
      "used 9 iterations (1.662s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (1.302s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 29 iterations (0.452s) to cluster 5010 items into 50 clusters\n",
      "used 40 iterations (0.857s) to cluster 5010 items into 100 clusters\n",
      "used 28 iterations (0.853s) to cluster 5010 items into 250 clusters\n",
      "used 9 iterations (0.407s) to cluster 5010 items into 500 clusters\n",
      "used 7 iterations (0.483s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.789s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.942s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (1.122s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (1.122s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (1.11s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 16 iterations (0.07s) to cluster 5010 items into 50 clusters\n",
      "used 27 iterations (0.264s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.29s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.36s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.464s) to cluster 5010 items into 750 clusters\n",
      "used 13 iterations (0.93s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.581s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (1.082s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.72s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.948s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 100 iterations (0.754s) to cluster 8173 items into 50 clusters\n",
      "used 86 iterations (0.844s) to cluster 8173 items into 100 clusters\n",
      "used 47 iterations (1.454s) to cluster 8173 items into 250 clusters\n",
      "used 29 iterations (1.422s) to cluster 8173 items into 500 clusters\n",
      "used 25 iterations (1.789s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.224s) to cluster 8173 items into 1000 clusters\n",
      "used 14 iterations (2.203s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.886s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (2.267s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (2.231s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 46 iterations (0.481s) to cluster 8173 items into 50 clusters\n",
      "used 55 iterations (0.533s) to cluster 8173 items into 100 clusters\n",
      "used 52 iterations (1.453s) to cluster 8173 items into 250 clusters\n",
      "used 26 iterations (1.303s) to cluster 8173 items into 500 clusters\n",
      "used 16 iterations (1.22s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.381s) to cluster 8173 items into 1000 clusters\n",
      "used 15 iterations (2.184s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.887s) to cluster 8173 items into 2000 clusters\n",
      "used 11 iterations (2.635s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (2.328s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 26 iterations (0.278s) to cluster 8173 items into 50 clusters\n",
      "used 40 iterations (0.393s) to cluster 8173 items into 100 clusters\n",
      "used 26 iterations (0.614s) to cluster 8173 items into 250 clusters\n",
      "used 18 iterations (0.984s) to cluster 8173 items into 500 clusters\n",
      "used 20 iterations (1.667s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (1.281s) to cluster 8173 items into 1000 clusters\n",
      "used 19 iterations (2.941s) to cluster 8173 items into 1500 clusters\n",
      "used 100 iterations (19.991s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (24.909s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (29.659s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 67 iterations (0.585s) to cluster 8173 items into 50 clusters\n",
      "used 35 iterations (0.339s) to cluster 8173 items into 100 clusters\n",
      "used 37 iterations (0.886s) to cluster 8173 items into 250 clusters\n",
      "used 19 iterations (0.999s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (1.307s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (1.474s) to cluster 8173 items into 1000 clusters\n",
      "used 12 iterations (1.915s) to cluster 8173 items into 1500 clusters\n",
      "used 13 iterations (2.443s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (2.022s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (29.771s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 38 iterations (1.642s) to cluster 8173 items into 50 clusters\n",
      "used 30 iterations (1.438s) to cluster 8173 items into 100 clusters\n",
      "used 20 iterations (1.243s) to cluster 8173 items into 250 clusters\n",
      "used 16 iterations (1.565s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (2.14s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (2.624s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (2.758s) to cluster 8173 items into 1500 clusters\n",
      "used 6 iterations (1.993s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.686s) to cluster 8173 items into 2500 clusters\n",
      "used 5 iterations (2.078s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 36 iterations (1.574s) to cluster 8173 items into 50 clusters\n",
      "used 42 iterations (2.001s) to cluster 8173 items into 100 clusters\n",
      "used 49 iterations (3.03s) to cluster 8173 items into 250 clusters\n",
      "used 19 iterations (2.26s) to cluster 8173 items into 500 clusters\n",
      "used 12 iterations (1.745s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (2.758s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (2.567s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (2.097s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (2.957s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (2.694s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 44 iterations (1.909s) to cluster 8173 items into 50 clusters\n",
      "used 34 iterations (1.628s) to cluster 8173 items into 100 clusters\n",
      "used 26 iterations (1.642s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (2.057s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (1.962s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (2.16s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (2.803s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (2.307s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.654s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (2.667s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 38 iterations (0.727s) to cluster 8173 items into 50 clusters\n",
      "used 35 iterations (0.835s) to cluster 8173 items into 100 clusters\n",
      "used 49 iterations (2.022s) to cluster 8173 items into 250 clusters\n",
      "used 21 iterations (1.463s) to cluster 8173 items into 500 clusters\n",
      "used 12 iterations (1.217s) to cluster 8173 items into 750 clusters\n",
      "used 17 iterations (2.231s) to cluster 8173 items into 1000 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 11 iterations (2.019s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.934s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (3.126s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.525s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (0.947s) to cluster 8173 items into 50 clusters\n",
      "used 29 iterations (1.003s) to cluster 8173 items into 100 clusters\n",
      "used 18 iterations (0.862s) to cluster 8173 items into 250 clusters\n",
      "used 18 iterations (1.508s) to cluster 8173 items into 500 clusters\n",
      "used 12 iterations (1.495s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (2.394s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (2.22s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (2.06s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (3.06s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.895s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.289s) to cluster 8173 items into 50 clusters\n",
      "used 26 iterations (0.385s) to cluster 8173 items into 100 clusters\n",
      "used 40 iterations (1.066s) to cluster 8173 items into 250 clusters\n",
      "used 30 iterations (1.913s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (1.405s) to cluster 8173 items into 750 clusters\n",
      "used 16 iterations (1.672s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.545s) to cluster 8173 items into 1500 clusters\n",
      "used 11 iterations (2.23s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (2.309s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (2.53s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.036s) to cluster 5010 items into 50 clusters\n",
      "used 23 iterations (0.142s) to cluster 5010 items into 100 clusters\n",
      "used 14 iterations (0.201s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.379s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (0.647s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.465s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.824s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (0.92s) to cluster 5010 items into 2000 clusters\n",
      "used 8 iterations (1.415s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.767s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 26 iterations (0.033s) to cluster 5010 items into 50 clusters\n",
      "used 13 iterations (0.084s) to cluster 5010 items into 100 clusters\n",
      "used 12 iterations (0.167s) to cluster 5010 items into 250 clusters\n",
      "used 11 iterations (0.281s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.437s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.715s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.696s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (1.127s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.963s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (1.001s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.246s) to cluster 5010 items into 50 clusters\n",
      "used 24 iterations (0.16s) to cluster 5010 items into 100 clusters\n",
      "used 22 iterations (0.309s) to cluster 5010 items into 250 clusters\n",
      "used 16 iterations (0.512s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.684s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.524s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.817s) to cluster 5010 items into 1500 clusters\n",
      "used 100 iterations (12.465s) to cluster 5010 items into 2000 clusters\n",
      "used 100 iterations (15.599s) to cluster 5010 items into 2500 clusters\n",
      "used 9 iterations (1.629s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.045s) to cluster 5010 items into 50 clusters\n",
      "used 23 iterations (0.148s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.232s) to cluster 5010 items into 250 clusters\n",
      "used 29 iterations (0.984s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (0.726s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.534s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.547s) to cluster 5010 items into 1500 clusters\n",
      "used 10 iterations (1.234s) to cluster 5010 items into 2000 clusters\n",
      "used 9 iterations (1.29s) to cluster 5010 items into 2500 clusters\n",
      "used 7 iterations (1.483s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 33 iterations (0.912s) to cluster 5010 items into 50 clusters\n",
      "used 34 iterations (1.023s) to cluster 5010 items into 100 clusters\n",
      "used 16 iterations (0.631s) to cluster 5010 items into 250 clusters\n",
      "used 11 iterations (0.694s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (1.322s) to cluster 5010 items into 750 clusters\n",
      "used 7 iterations (0.958s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.875s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (1.1952s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.877s) to cluster 5010 items into 2500 clusters\n",
      "used 3 iterations (0.909s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 32 iterations (0.768s) to cluster 5010 items into 50 clusters\n",
      "used 29 iterations (0.871s) to cluster 5010 items into 100 clusters\n",
      "used 15 iterations (0.594s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.761s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (1.119s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (1.581s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.882s) to cluster 5010 items into 1500 clusters\n",
      "used 4 iterations (0.936s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (1.08s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (1.142s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 33 iterations (0.799s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.734s) to cluster 5010 items into 100 clusters\n",
      "used 18 iterations (0.73s) to cluster 5010 items into 250 clusters\n",
      "used 19 iterations (1.207s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (1.145s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.838s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (1.204s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (1.851s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (1.3s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (1.23s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (0.335s) to cluster 5010 items into 50 clusters\n",
      "used 26 iterations (0.387s) to cluster 5010 items into 100 clusters\n",
      "used 18 iterations (0.418s) to cluster 5010 items into 250 clusters\n",
      "used 18 iterations (0.878s) to cluster 5010 items into 500 clusters\n",
      "used 17 iterations (0.868s) to cluster 5010 items into 750 clusters\n",
      "used 13 iterations (1.333s) to cluster 5010 items into 1000 clusters\n",
      "used 13 iterations (1.554s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (1.26s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (1.196s) to cluster 5010 items into 2500 clusters\n",
      "used 7 iterations (1.571s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 40 iterations (0.645s) to cluster 5010 items into 50 clusters\n",
      "used 17 iterations (0.361s) to cluster 5010 items into 100 clusters\n",
      "used 20 iterations (0.598s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.585s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.617s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.986s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (1.206s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (1.275s) to cluster 5010 items into 2000 clusters\n",
      "used 8 iterations (1.627s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (1.08s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 12 iterations (0.053s) to cluster 5010 items into 50 clusters\n",
      "used 16 iterations (0.156s) to cluster 5010 items into 100 clusters\n",
      "used 11 iterations (0.186s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.666s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.43s) to cluster 5010 items into 750 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 6 iterations (0.339s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.687s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.87s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.876s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.679s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 91 iterations (0.709s) to cluster 8175 items into 50 clusters\n",
      "used 85 iterations (0.838s) to cluster 8175 items into 100 clusters\n",
      "used 50 iterations (1.289s) to cluster 8175 items into 250 clusters\n",
      "used 32 iterations (1.57s) to cluster 8175 items into 500 clusters\n",
      "used 20 iterations (1.665s) to cluster 8175 items into 750 clusters\n",
      "used 16 iterations (1.756s) to cluster 8175 items into 1000 clusters\n",
      "used 17 iterations (2.405s) to cluster 8175 items into 1500 clusters\n",
      "used 8 iterations (1.532s) to cluster 8175 items into 2000 clusters\n",
      "used 8 iterations (2.04s) to cluster 8175 items into 2500 clusters\n",
      "used 8 iterations (2.19s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 89 iterations (0.705s) to cluster 8175 items into 50 clusters\n",
      "used 40 iterations (0.392s) to cluster 8175 items into 100 clusters\n",
      "used 57 iterations (1.444s) to cluster 8175 items into 250 clusters\n",
      "used 23 iterations (1.158s) to cluster 8175 items into 500 clusters\n",
      "used 22 iterations (1.798s) to cluster 8175 items into 750 clusters\n",
      "used 15 iterations (1.473s) to cluster 8175 items into 1000 clusters\n",
      "used 17 iterations (2.585s) to cluster 8175 items into 1500 clusters\n",
      "used 8 iterations (1.525s) to cluster 8175 items into 2000 clusters\n",
      "used 8 iterations (1.942s) to cluster 8175 items into 2500 clusters\n",
      "used 8 iterations (2.176s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 36 iterations (0.196s) to cluster 8175 items into 50 clusters\n",
      "used 28 iterations (0.273s) to cluster 8175 items into 100 clusters\n",
      "used 33 iterations (0.708s) to cluster 8175 items into 250 clusters\n",
      "used 28 iterations (1.369s) to cluster 8175 items into 500 clusters\n",
      "used 17 iterations (1.414s) to cluster 8175 items into 750 clusters\n",
      "used 21 iterations (2.199s) to cluster 8175 items into 1000 clusters\n",
      "used 15 iterations (2.191s) to cluster 8175 items into 1500 clusters\n",
      "used 21 iterations (4.112s) to cluster 8175 items into 2000 clusters\n",
      "used 100 iterations (24.753s) to cluster 8175 items into 2500 clusters\n",
      "used 100 iterations (29.647s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 56 iterations (0.308s) to cluster 8175 items into 50 clusters\n",
      "used 49 iterations (0.687s) to cluster 8175 items into 100 clusters\n",
      "used 24 iterations (0.501s) to cluster 8175 items into 250 clusters\n",
      "used 20 iterations (1.052s) to cluster 8175 items into 500 clusters\n",
      "used 15 iterations (1.169s) to cluster 8175 items into 750 clusters\n",
      "used 15 iterations (1.475s) to cluster 8175 items into 1000 clusters\n",
      "used 11 iterations (1.563s) to cluster 8175 items into 1500 clusters\n",
      "used 100 iterations (19.702s) to cluster 8175 items into 2000 clusters\n",
      "used 8 iterations (2.021s) to cluster 8175 items into 2500 clusters\n",
      "used 7 iterations (1.954s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 40 iterations (1.736s) to cluster 8175 items into 50 clusters\n",
      "used 39 iterations (1.852s) to cluster 8175 items into 100 clusters\n",
      "used 24 iterations (1.493s) to cluster 8175 items into 250 clusters\n",
      "used 18 iterations (1.937s) to cluster 8175 items into 500 clusters\n",
      "used 18 iterations (2.697s) to cluster 8175 items into 750 clusters\n",
      "used 9 iterations (1.607s) to cluster 8175 items into 1000 clusters\n",
      "used 11 iterations (2.717s) to cluster 8175 items into 1500 clusters\n",
      "used 9 iterations (2.843s) to cluster 8175 items into 2000 clusters\n",
      "used 8 iterations (3.18s) to cluster 8175 items into 2500 clusters\n",
      "used 5 iterations (2.058s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 58 iterations (2.509s) to cluster 8175 items into 50 clusters\n",
      "used 31 iterations (1.471s) to cluster 8175 items into 100 clusters\n",
      "used 29 iterations (1.813s) to cluster 8175 items into 250 clusters\n",
      "used 17 iterations (2.071s) to cluster 8175 items into 500 clusters\n",
      "used 18 iterations (2.717s) to cluster 8175 items into 750 clusters\n",
      "used 10 iterations (1.769s) to cluster 8175 items into 1000 clusters\n",
      "used 10 iterations (2.56s) to cluster 8175 items into 1500 clusters\n",
      "used 10 iterations (3.095s) to cluster 8175 items into 2000 clusters\n",
      "used 7 iterations (2.59s) to cluster 8175 items into 2500 clusters\n",
      "used 8 iterations (3.421s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (1.532s) to cluster 8175 items into 50 clusters\n",
      "used 59 iterations (2.777s) to cluster 8175 items into 100 clusters\n",
      "used 29 iterations (1.78s) to cluster 8175 items into 250 clusters\n",
      "used 15 iterations (1.744s) to cluster 8175 items into 500 clusters\n",
      "used 14 iterations (2.201s) to cluster 8175 items into 750 clusters\n",
      "used 12 iterations (2.302s) to cluster 8175 items into 1000 clusters\n",
      "used 11 iterations (2.727s) to cluster 8175 items into 1500 clusters\n",
      "used 10 iterations (3.096s) to cluster 8175 items into 2000 clusters\n",
      "used 7 iterations (2.671s) to cluster 8175 items into 2500 clusters\n",
      "used 7 iterations (3.073s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 32 iterations (0.6s) to cluster 8175 items into 50 clusters\n",
      "used 39 iterations (0.93s) to cluster 8175 items into 100 clusters\n",
      "used 25 iterations (0.904s) to cluster 8175 items into 250 clusters\n",
      "used 17 iterations (1.027s) to cluster 8175 items into 500 clusters\n",
      "used 16 iterations (1.739s) to cluster 8175 items into 750 clusters\n",
      "used 15 iterations (2.048s) to cluster 8175 items into 1000 clusters\n",
      "used 13 iterations (2.451s) to cluster 8175 items into 1500 clusters\n",
      "used 7 iterations (1.796s) to cluster 8175 items into 2000 clusters\n",
      "used 8 iterations (2.397s) to cluster 8175 items into 2500 clusters\n",
      "used 5 iterations (1.489s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.834s) to cluster 8175 items into 50 clusters\n",
      "used 31 iterations (1.069s) to cluster 8175 items into 100 clusters\n",
      "used 37 iterations (1.76s) to cluster 8175 items into 250 clusters\n",
      "used 15 iterations (1.301s) to cluster 8175 items into 500 clusters\n",
      "used 13 iterations (1.588s) to cluster 8175 items into 750 clusters\n",
      "used 11 iterations (1.687s) to cluster 8175 items into 1000 clusters\n",
      "used 8 iterations (1.7s) to cluster 8175 items into 1500 clusters\n",
      "used 8 iterations (2.294s) to cluster 8175 items into 2000 clusters\n",
      "used 8 iterations (2.629s) to cluster 8175 items into 2500 clusters\n",
      "used 6 iterations (2.279s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 17 iterations (0.175s) to cluster 8175 items into 50 clusters\n",
      "used 28 iterations (0.409s) to cluster 8175 items into 100 clusters\n",
      "used 25 iterations (0.675s) to cluster 8175 items into 250 clusters\n",
      "used 15 iterations (0.936s) to cluster 8175 items into 500 clusters\n",
      "used 20 iterations (1.554s) to cluster 8175 items into 750 clusters\n",
      "used 16 iterations (1.918s) to cluster 8175 items into 1000 clusters\n",
      "used 14 iterations (2.304s) to cluster 8175 items into 1500 clusters\n",
      "used 10 iterations (1.963s) to cluster 8175 items into 2000 clusters\n",
      "used 9 iterations (2.553s) to cluster 8175 items into 2500 clusters\n",
      "used 7 iterations (2.259s) to cluster 8175 items into 3000 clusters\n",
      "Completed.\n",
      "used 25 iterations (0.041s) to cluster 5010 items into 50 clusters\n",
      "used 23 iterations (0.157s) to cluster 5010 items into 100 clusters\n",
      "used 18 iterations (0.261s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.337s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (0.44s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.476s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.994s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (1.029s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.961s) to cluster 5010 items into 2500 clusters\n",
      "used 7 iterations (1.501s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 24 iterations (0.042s) to cluster 5010 items into 50 clusters\n",
      "used 14 iterations (0.107s) to cluster 5010 items into 100 clusters\n",
      "used 16 iterations (0.229s) to cluster 5010 items into 250 clusters\n",
      "used 10 iterations (0.477s) to cluster 5010 items into 500 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 10 iterations (0.395s) to cluster 5010 items into 750 clusters\n",
      "used 12 iterations (40.788s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (1.445s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (6.9692s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (5.8761s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (2.2681s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 19 iterations (1.004s) to cluster 5010 items into 50 clusters\n",
      "used 26 iterations (0.829s) to cluster 5010 items into 100 clusters\n",
      "used 24 iterations (2.1177s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (2.2193s) to cluster 5010 items into 500 clusters\n",
      "used 18 iterations (0.833s) to cluster 5010 items into 750 clusters\n",
      "used 14 iterations (1.028s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.775s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.717s) to cluster 5010 items into 2000 clusters\n",
      "used 13 iterations (1.617s) to cluster 5010 items into 2500 clusters\n",
      "used 100 iterations (16.34s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 40 iterations (0.086s) to cluster 5010 items into 50 clusters\n",
      "used 30 iterations (0.207s) to cluster 5010 items into 100 clusters\n",
      "used 20 iterations (0.489s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (2.103s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.395s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.527s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.688s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (1.325s) to cluster 5010 items into 2000 clusters\n",
      "used 100 iterations (15.434s) to cluster 5010 items into 2500 clusters\n",
      "used 9 iterations (1.144s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 38 iterations (1.146s) to cluster 5010 items into 50 clusters\n",
      "used 22 iterations (0.958s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.938s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (1.124s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.755s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.815s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.695s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.653s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.819s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.689s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 29 iterations (0.493s) to cluster 5010 items into 50 clusters\n",
      "used 29 iterations (0.625s) to cluster 5010 items into 100 clusters\n",
      "used 12 iterations (0.34s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.635s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.756s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.83s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.613s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.662s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.656s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.816s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 26 iterations (0.482s) to cluster 5010 items into 50 clusters\n",
      "used 22 iterations (0.508s) to cluster 5010 items into 100 clusters\n",
      "used 14 iterations (0.447s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.695s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (0.879s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.743s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.801s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (1.003s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.861s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.818s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (0.267s) to cluster 5010 items into 50 clusters\n",
      "used 34 iterations (0.455s) to cluster 5010 items into 100 clusters\n",
      "used 26 iterations (0.536s) to cluster 5010 items into 250 clusters\n",
      "used 22 iterations (0.627s) to cluster 5010 items into 500 clusters\n",
      "used 16 iterations (0.643s) to cluster 5010 items into 750 clusters\n",
      "used 13 iterations (0.76s) to cluster 5010 items into 1000 clusters\n",
      "used 14 iterations (1.099s) to cluster 5010 items into 1500 clusters\n",
      "used 20 iterations (1.99s) to cluster 5010 items into 2000 clusters\n",
      "used 11 iterations (2.079s) to cluster 5010 items into 2500 clusters\n",
      "used 8 iterations (2.573s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 21 iterations (0.216s) to cluster 5010 items into 50 clusters\n",
      "used 40 iterations (0.862s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.615s) to cluster 5010 items into 250 clusters\n",
      "used 10 iterations (0.455s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.73s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.729s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (1.336s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (1.484s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.737s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (1.112s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 14 iterations (0.065s) to cluster 5010 items into 50 clusters\n",
      "used 19 iterations (0.152s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.204s) to cluster 5010 items into 250 clusters\n",
      "used 10 iterations (0.188s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.382s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.518s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.545s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (1.129s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.748s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (1.029s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 69 iterations (0.32s) to cluster 8173 items into 50 clusters\n",
      "used 99 iterations (0.71s) to cluster 8173 items into 100 clusters\n",
      "used 42 iterations (0.689s) to cluster 8173 items into 250 clusters\n",
      "used 30 iterations (1.254s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (1.272s) to cluster 8173 items into 750 clusters\n",
      "used 26 iterations (2.269s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.515s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.643s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.601s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.348s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 46 iterations (0.444s) to cluster 8173 items into 50 clusters\n",
      "used 53 iterations (0.415s) to cluster 8173 items into 100 clusters\n",
      "used 27 iterations (0.38s) to cluster 8173 items into 250 clusters\n",
      "used 38 iterations (1.976s) to cluster 8173 items into 500 clusters\n",
      "used 22 iterations (1.221s) to cluster 8173 items into 750 clusters\n",
      "used 19 iterations (1.544s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.977s) to cluster 8173 items into 1500 clusters\n",
      "used 11 iterations (2.348s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.841s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.23s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 22 iterations (0.094s) to cluster 8173 items into 50 clusters\n",
      "used 29 iterations (0.205s) to cluster 8173 items into 100 clusters\n",
      "used 34 iterations (0.814s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (0.531s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (1.243s) to cluster 8173 items into 750 clusters\n",
      "used 17 iterations (1.187s) to cluster 8173 items into 1000 clusters\n",
      "used 100 iterations (23.693s) to cluster 8173 items into 1500 clusters\n",
      "used 13 iterations (1.446s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (15.655s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (19.623s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.12s) to cluster 8173 items into 50 clusters\n",
      "used 49 iterations (0.552s) to cluster 8173 items into 100 clusters\n",
      "used 42 iterations (0.618s) to cluster 8173 items into 250 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 25 iterations (0.925s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (0.808s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (1.065s) to cluster 8173 items into 1000 clusters\n",
      "used 14 iterations (1.364s) to cluster 8173 items into 1500 clusters\n",
      "used 12 iterations (1.475s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (16.186s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (1.718s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 36 iterations (1.116s) to cluster 8173 items into 50 clusters\n",
      "used 41 iterations (1.417s) to cluster 8173 items into 100 clusters\n",
      "used 23 iterations (1.035s) to cluster 8173 items into 250 clusters\n",
      "used 14 iterations (1.028s) to cluster 8173 items into 500 clusters\n",
      "used 12 iterations (1.346s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.624s) to cluster 8173 items into 1000 clusters\n",
      "used 9 iterations (1.647s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (2.264s) to cluster 8173 items into 2000 clusters\n",
      "used 6 iterations (1.738s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.811s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 46 iterations (1.384s) to cluster 8173 items into 50 clusters\n",
      "used 34 iterations (1.173s) to cluster 8173 items into 100 clusters\n",
      "used 37 iterations (1.576s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (1.446s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (1.501s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.443s) to cluster 8173 items into 1000 clusters\n",
      "used 8 iterations (1.578s) to cluster 8173 items into 1500 clusters\n",
      "used 6 iterations (1.159s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (2.251s) to cluster 8173 items into 2500 clusters\n",
      "used 5 iterations (1.52s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 26 iterations (0.789s) to cluster 8173 items into 50 clusters\n",
      "used 34 iterations (1.15s) to cluster 8173 items into 100 clusters\n",
      "used 18 iterations (0.823s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (1.219s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.388s) to cluster 8173 items into 750 clusters\n",
      "used 10 iterations (1.306s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (2.011s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.622s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (2.409s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.212s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 34 iterations (0.45s) to cluster 8173 items into 50 clusters\n",
      "used 57 iterations (0.955s) to cluster 8173 items into 100 clusters\n",
      "used 33 iterations (0.826s) to cluster 8173 items into 250 clusters\n",
      "used 24 iterations (1.007s) to cluster 8173 items into 500 clusters\n",
      "used 18 iterations (1.286s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.151s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.462s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.341s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.56s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (1.62s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 54 iterations (1.148s) to cluster 8173 items into 50 clusters\n",
      "used 35 iterations (0.843s) to cluster 8173 items into 100 clusters\n",
      "used 23 iterations (0.796s) to cluster 8173 items into 250 clusters\n",
      "used 28 iterations (1.402s) to cluster 8173 items into 500 clusters\n",
      "used 16 iterations (1.668s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.276s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.603s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.381s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (2.213s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.603s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 19 iterations (0.136s) to cluster 8173 items into 50 clusters\n",
      "used 32 iterations (0.324s) to cluster 8173 items into 100 clusters\n",
      "used 22 iterations (0.395s) to cluster 8173 items into 250 clusters\n",
      "used 30 iterations (0.983s) to cluster 8173 items into 500 clusters\n",
      "used 19 iterations (1.097s) to cluster 8173 items into 750 clusters\n",
      "used 13 iterations (0.876s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.209s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.267s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (1.838s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (1.977s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 24 iterations (0.022s) to cluster 5010 items into 50 clusters\n",
      "used 21 iterations (0.092s) to cluster 5010 items into 100 clusters\n",
      "used 24 iterations (0.22s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.201s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.32s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.37s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.662s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (0.656s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.714s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (0.8s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 18 iterations (0.022s) to cluster 5010 items into 50 clusters\n",
      "used 18 iterations (0.08s) to cluster 5010 items into 100 clusters\n",
      "used 15 iterations (0.141s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.249s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.461s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.356s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.422s) to cluster 5010 items into 1500 clusters\n",
      "used 10 iterations (0.885s) to cluster 5010 items into 2000 clusters\n",
      "used 7 iterations (0.782s) to cluster 5010 items into 2500 clusters\n",
      "used 7 iterations (0.887s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 37 iterations (0.046s) to cluster 5010 items into 50 clusters\n",
      "used 22 iterations (0.097s) to cluster 5010 items into 100 clusters\n",
      "used 19 iterations (0.17s) to cluster 5010 items into 250 clusters\n",
      "used 23 iterations (0.384s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (0.495s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.325s) to cluster 5010 items into 1000 clusters\n",
      "used 12 iterations (0.613s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (0.865s) to cluster 5010 items into 2000 clusters\n",
      "used 10 iterations (1.051s) to cluster 5010 items into 2500 clusters\n",
      "used 100 iterations (12.093s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 33 iterations (0.042s) to cluster 5010 items into 50 clusters\n",
      "used 22 iterations (0.097s) to cluster 5010 items into 100 clusters\n",
      "used 21 iterations (0.195s) to cluster 5010 items into 250 clusters\n",
      "used 21 iterations (0.597s) to cluster 5010 items into 500 clusters\n",
      "used 14 iterations (0.365s) to cluster 5010 items into 750 clusters\n",
      "used 15 iterations (0.529s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.725s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (0.906s) to cluster 5010 items into 2000 clusters\n",
      "used 11 iterations (0.921s) to cluster 5010 items into 2500 clusters\n",
      "used 8 iterations (1.182s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 29 iterations (0.473s) to cluster 5010 items into 50 clusters\n",
      "used 19 iterations (0.407s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.462s) to cluster 5010 items into 250 clusters\n",
      "used 10 iterations (0.472s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (0.807s) to cluster 5010 items into 750 clusters\n",
      "used 7 iterations (0.526s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.634s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.653s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.908s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.9s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 39 iterations (0.664s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.527s) to cluster 5010 items into 100 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 15 iterations (0.43s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.651s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (0.674s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.686s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.714s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.852s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (1.139s) to cluster 5010 items into 2500 clusters\n",
      "used 3 iterations (0.515s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 48 iterations (0.817s) to cluster 5010 items into 50 clusters\n",
      "used 27 iterations (0.562s) to cluster 5010 items into 100 clusters\n",
      "used 14 iterations (0.403s) to cluster 5010 items into 250 clusters\n",
      "used 16 iterations (0.725s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.518s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.662s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (1.272s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.631s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (1.009s) to cluster 5010 items into 2500 clusters\n",
      "used 3 iterations (0.552s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 24 iterations (0.165s) to cluster 5010 items into 50 clusters\n",
      "used 24 iterations (0.258s) to cluster 5010 items into 100 clusters\n",
      "used 22 iterations (0.376s) to cluster 5010 items into 250 clusters\n",
      "used 17 iterations (0.45s) to cluster 5010 items into 500 clusters\n",
      "used 15 iterations (0.757s) to cluster 5010 items into 750 clusters\n",
      "used 17 iterations (0.873s) to cluster 5010 items into 1000 clusters\n",
      "used 12 iterations (0.982s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (1.135s) to cluster 5010 items into 2000 clusters\n",
      "used 9 iterations (1.002s) to cluster 5010 items into 2500 clusters\n",
      "used 9 iterations (1.452s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.34s) to cluster 5010 items into 50 clusters\n",
      "used 18 iterations (0.267s) to cluster 5010 items into 100 clusters\n",
      "used 16 iterations (0.326s) to cluster 5010 items into 250 clusters\n",
      "used 20 iterations (0.639s) to cluster 5010 items into 500 clusters\n",
      "used 8 iterations (0.379s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.67s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.804s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.551s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.663s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (1.125s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 15 iterations (0.048s) to cluster 5010 items into 50 clusters\n",
      "used 17 iterations (0.117s) to cluster 5010 items into 100 clusters\n",
      "used 24 iterations (0.279s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.237s) to cluster 5010 items into 500 clusters\n",
      "used 14 iterations (0.401s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.439s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.558s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.646s) to cluster 5010 items into 2000 clusters\n",
      "used 7 iterations (0.625s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.561s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 64 iterations (0.262s) to cluster 8173 items into 50 clusters\n",
      "used 100 iterations (0.88s) to cluster 8173 items into 100 clusters\n",
      "used 41 iterations (0.58s) to cluster 8173 items into 250 clusters\n",
      "used 31 iterations (1.042s) to cluster 8173 items into 500 clusters\n",
      "used 21 iterations (1.102s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (0.668s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (0.842s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.366s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.28s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (1.662s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 46 iterations (0.19s) to cluster 8173 items into 50 clusters\n",
      "used 74 iterations (0.495s) to cluster 8173 items into 100 clusters\n",
      "used 55 iterations (0.963s) to cluster 8173 items into 250 clusters\n",
      "used 30 iterations (1.043s) to cluster 8173 items into 500 clusters\n",
      "used 22 iterations (1.128s) to cluster 8173 items into 750 clusters\n",
      "used 17 iterations (1.129s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (1.209s) to cluster 8173 items into 1500 clusters\n",
      "used 13 iterations (1.787s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (1.394s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (1.29s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 40 iterations (0.171s) to cluster 8173 items into 50 clusters\n",
      "used 23 iterations (0.157s) to cluster 8173 items into 100 clusters\n",
      "used 42 iterations (0.797s) to cluster 8173 items into 250 clusters\n",
      "used 26 iterations (0.706s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (0.991s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.005s) to cluster 8173 items into 1000 clusters\n",
      "used 16 iterations (2.424s) to cluster 8173 items into 1500 clusters\n",
      "used 38 iterations (7.608s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (16.557s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (18.992s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (0.129s) to cluster 8173 items into 50 clusters\n",
      "used 46 iterations (0.522s) to cluster 8173 items into 100 clusters\n",
      "used 44 iterations (0.808s) to cluster 8173 items into 250 clusters\n",
      "used 18 iterations (0.499s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (0.598s) to cluster 8173 items into 750 clusters\n",
      "used 21 iterations (1.377s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.025s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.262s) to cluster 8173 items into 2000 clusters\n",
      "used 12 iterations (1.986s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (19.0881s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 41 iterations (1.262s) to cluster 8173 items into 50 clusters\n",
      "used 38 iterations (1.251s) to cluster 8173 items into 100 clusters\n",
      "used 25 iterations (1.087s) to cluster 8173 items into 250 clusters\n",
      "used 16 iterations (1.107s) to cluster 8173 items into 500 clusters\n",
      "used 13 iterations (1.259s) to cluster 8173 items into 750 clusters\n",
      "used 10 iterations (1.36s) to cluster 8173 items into 1000 clusters\n",
      "used 12 iterations (2.262s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.522s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.797s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (2.003s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 55 iterations (1.665s) to cluster 8173 items into 50 clusters\n",
      "used 30 iterations (1.007s) to cluster 8173 items into 100 clusters\n",
      "used 33 iterations (1.404s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (1.529s) to cluster 8173 items into 500 clusters\n",
      "used 11 iterations (1.242s) to cluster 8173 items into 750 clusters\n",
      "used 18 iterations (2.464s) to cluster 8173 items into 1000 clusters\n",
      "used 14 iterations (2.378s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.909s) to cluster 8173 items into 2000 clusters\n",
      "used 11 iterations (3.147s) to cluster 8173 items into 2500 clusters\n",
      "used 5 iterations (1.519s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 37 iterations (1.123s) to cluster 8173 items into 50 clusters\n",
      "used 26 iterations (0.875s) to cluster 8173 items into 100 clusters\n",
      "used 20 iterations (0.886s) to cluster 8173 items into 250 clusters\n",
      "used 21 iterations (1.445s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.361s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.671s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.644s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (2.127s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (2.247s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.067s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (0.471s) to cluster 8173 items into 50 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 38 iterations (0.614s) to cluster 8173 items into 100 clusters\n",
      "used 35 iterations (0.863s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (0.85s) to cluster 8173 items into 500 clusters\n",
      "used 25 iterations (1.643s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.141s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.325s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.114s) to cluster 8173 items into 2000 clusters\n",
      "used 6 iterations (0.986s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (2.218s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 43 iterations (0.915s) to cluster 8173 items into 50 clusters\n",
      "used 24 iterations (0.567s) to cluster 8173 items into 100 clusters\n",
      "used 32 iterations (1.071s) to cluster 8173 items into 250 clusters\n",
      "used 18 iterations (0.893s) to cluster 8173 items into 500 clusters\n",
      "used 11 iterations (0.815s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.179s) to cluster 8173 items into 1000 clusters\n",
      "used 9 iterations (1.363s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.585s) to cluster 8173 items into 2000 clusters\n",
      "used 6 iterations (1.201s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.8s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 36 iterations (0.257s) to cluster 8173 items into 50 clusters\n",
      "used 34 iterations (0.354s) to cluster 8173 items into 100 clusters\n",
      "used 23 iterations (0.418s) to cluster 8173 items into 250 clusters\n",
      "used 18 iterations (0.79s) to cluster 8173 items into 500 clusters\n",
      "used 21 iterations (1.268s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.102s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.008s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.478s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.402s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (1.995s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 20 iterations (0.025s) to cluster 5012 items into 50 clusters\n",
      "used 14 iterations (0.063s) to cluster 5012 items into 100 clusters\n",
      "used 16 iterations (0.145s) to cluster 5012 items into 250 clusters\n",
      "used 17 iterations (0.493s) to cluster 5012 items into 500 clusters\n",
      "used 10 iterations (0.251s) to cluster 5012 items into 750 clusters\n",
      "used 12 iterations (0.403s) to cluster 5012 items into 1000 clusters\n",
      "used 8 iterations (0.619s) to cluster 5012 items into 1500 clusters\n",
      "used 6 iterations (0.402s) to cluster 5012 items into 2000 clusters\n",
      "used 7 iterations (0.807s) to cluster 5012 items into 2500 clusters\n",
      "used 5 iterations (0.503s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 16 iterations (0.022s) to cluster 5012 items into 50 clusters\n",
      "used 17 iterations (0.282s) to cluster 5012 items into 100 clusters\n",
      "used 12 iterations (0.109s) to cluster 5012 items into 250 clusters\n",
      "used 10 iterations (0.168s) to cluster 5012 items into 500 clusters\n",
      "used 8 iterations (0.197s) to cluster 5012 items into 750 clusters\n",
      "used 7 iterations (0.242s) to cluster 5012 items into 1000 clusters\n",
      "used 8 iterations (0.619s) to cluster 5012 items into 1500 clusters\n",
      "used 7 iterations (0.664s) to cluster 5012 items into 2000 clusters\n",
      "used 5 iterations (0.421s) to cluster 5012 items into 2500 clusters\n",
      "used 9 iterations (1.09s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 19 iterations (0.022s) to cluster 5012 items into 50 clusters\n",
      "used 20 iterations (0.087s) to cluster 5012 items into 100 clusters\n",
      "used 25 iterations (0.218s) to cluster 5012 items into 250 clusters\n",
      "used 19 iterations (0.531s) to cluster 5012 items into 500 clusters\n",
      "used 14 iterations (0.342s) to cluster 5012 items into 750 clusters\n",
      "used 12 iterations (0.408s) to cluster 5012 items into 1000 clusters\n",
      "used 7 iterations (0.572s) to cluster 5012 items into 1500 clusters\n",
      "used 8 iterations (0.546s) to cluster 5012 items into 2000 clusters\n",
      "used 14 iterations (1.403s) to cluster 5012 items into 2500 clusters\n",
      "used 100 iterations (12.156s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 23 iterations (0.03s) to cluster 5012 items into 50 clusters\n",
      "used 18 iterations (0.081s) to cluster 5012 items into 100 clusters\n",
      "used 19 iterations (0.174s) to cluster 5012 items into 250 clusters\n",
      "used 12 iterations (0.202s) to cluster 5012 items into 500 clusters\n",
      "used 15 iterations (0.392s) to cluster 5012 items into 750 clusters\n",
      "used 11 iterations (0.373s) to cluster 5012 items into 1000 clusters\n",
      "used 8 iterations (0.412s) to cluster 5012 items into 1500 clusters\n",
      "used 100 iterations (8.094s) to cluster 5012 items into 2000 clusters\n",
      "used 100 iterations (10.278s) to cluster 5012 items into 2500 clusters\n",
      "used 100 iterations (11.486s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 37 iterations (0.603s) to cluster 5012 items into 50 clusters\n",
      "used 24 iterations (0.503s) to cluster 5012 items into 100 clusters\n",
      "used 21 iterations (0.557s) to cluster 5012 items into 250 clusters\n",
      "used 10 iterations (0.462s) to cluster 5012 items into 500 clusters\n",
      "used 8 iterations (0.488s) to cluster 5012 items into 750 clusters\n",
      "used 7 iterations (0.524s) to cluster 5012 items into 1000 clusters\n",
      "used 6 iterations (0.63s) to cluster 5012 items into 1500 clusters\n",
      "used 6 iterations (0.769s) to cluster 5012 items into 2000 clusters\n",
      "used 5 iterations (1.002s) to cluster 5012 items into 2500 clusters\n",
      "used 5 iterations (0.861s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 27 iterations (0.437s) to cluster 5012 items into 50 clusters\n",
      "used 25 iterations (0.52s) to cluster 5012 items into 100 clusters\n",
      "used 15 iterations (0.434s) to cluster 5012 items into 250 clusters\n",
      "used 11 iterations (0.493s) to cluster 5012 items into 500 clusters\n",
      "used 10 iterations (0.615s) to cluster 5012 items into 750 clusters\n",
      "used 8 iterations (0.576s) to cluster 5012 items into 1000 clusters\n",
      "used 6 iterations (0.834s) to cluster 5012 items into 1500 clusters\n",
      "used 5 iterations (0.661s) to cluster 5012 items into 2000 clusters\n",
      "used 4 iterations (0.846s) to cluster 5012 items into 2500 clusters\n",
      "used 5 iterations (1.093s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 17 iterations (0.279s) to cluster 5012 items into 50 clusters\n",
      "used 23 iterations (0.48s) to cluster 5012 items into 100 clusters\n",
      "used 26 iterations (0.734s) to cluster 5012 items into 250 clusters\n",
      "used 17 iterations (0.763s) to cluster 5012 items into 500 clusters\n",
      "used 13 iterations (0.804s) to cluster 5012 items into 750 clusters\n",
      "used 9 iterations (0.677s) to cluster 5012 items into 1000 clusters\n",
      "used 7 iterations (0.922s) to cluster 5012 items into 1500 clusters\n",
      "used 7 iterations (0.882s) to cluster 5012 items into 2000 clusters\n",
      "used 5 iterations (0.98s) to cluster 5012 items into 2500 clusters\n",
      "used 3 iterations (0.762s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 22 iterations (0.149s) to cluster 5012 items into 50 clusters\n",
      "used 40 iterations (0.415s) to cluster 5012 items into 100 clusters\n",
      "used 30 iterations (0.5s) to cluster 5012 items into 250 clusters\n",
      "used 18 iterations (0.46s) to cluster 5012 items into 500 clusters\n",
      "used 14 iterations (0.675s) to cluster 5012 items into 750 clusters\n",
      "used 13 iterations (0.832s) to cluster 5012 items into 1000 clusters\n",
      "used 10 iterations (0.722s) to cluster 5012 items into 1500 clusters\n",
      "used 7 iterations (0.847s) to cluster 5012 items into 2000 clusters\n",
      "used 11 iterations (1.431s) to cluster 5012 items into 2500 clusters\n",
      "used 6 iterations (0.991s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 18 iterations (0.182s) to cluster 5012 items into 50 clusters\n",
      "used 22 iterations (0.316s) to cluster 5012 items into 100 clusters\n",
      "used 16 iterations (0.344s) to cluster 5012 items into 250 clusters\n",
      "used 16 iterations (0.503s) to cluster 5012 items into 500 clusters\n",
      "used 7 iterations (0.335s) to cluster 5012 items into 750 clusters\n",
      "used 8 iterations (0.489s) to cluster 5012 items into 1000 clusters\n",
      "used 7 iterations (0.65s) to cluster 5012 items into 1500 clusters\n",
      "used 5 iterations (0.831s) to cluster 5012 items into 2000 clusters\n",
      "used 5 iterations (0.672s) to cluster 5012 items into 2500 clusters\n",
      "used 4 iterations (0.68s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 16 iterations (0.052s) to cluster 5012 items into 50 clusters\n",
      "used 11 iterations (0.077s) to cluster 5012 items into 100 clusters\n",
      "used 21 iterations (0.243s) to cluster 5012 items into 250 clusters\n",
      "used 12 iterations (0.239s) to cluster 5012 items into 500 clusters\n",
      "used 14 iterations (0.404s) to cluster 5012 items into 750 clusters\n",
      "used 7 iterations (0.476s) to cluster 5012 items into 1000 clusters\n",
      "used 7 iterations (0.394s) to cluster 5012 items into 1500 clusters\n",
      "used 7 iterations (0.668s) to cluster 5012 items into 2000 clusters\n",
      "used 6 iterations (0.537s) to cluster 5012 items into 2500 clusters\n",
      "used 4 iterations (0.645s) to cluster 5012 items into 3000 clusters\n",
      "Completed.\n",
      "used 93 iterations (0.372s) to cluster 8173 items into 50 clusters\n",
      "used 84 iterations (0.56s) to cluster 8173 items into 100 clusters\n",
      "used 54 iterations (0.9708s) to cluster 8173 items into 250 clusters\n",
      "used 26 iterations (0.916s) to cluster 8173 items into 500 clusters\n",
      "used 18 iterations (0.954s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (0.971s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.019s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (0.976s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (1.503s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.371s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 79 iterations (0.32s) to cluster 8173 items into 50 clusters\n",
      "used 58 iterations (0.386s) to cluster 8173 items into 100 clusters\n",
      "used 29 iterations (0.401s) to cluster 8173 items into 250 clusters\n",
      "used 22 iterations (0.746s) to cluster 8173 items into 500 clusters\n",
      "used 20 iterations (1.052s) to cluster 8173 items into 750 clusters\n",
      "used 17 iterations (1.16s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.095s) to cluster 8173 items into 1500 clusters\n",
      "used 15 iterations (1.938s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (1.617s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (1.441s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 69 iterations (0.615s) to cluster 8173 items into 50 clusters\n",
      "used 33 iterations (0.216s) to cluster 8173 items into 100 clusters\n",
      "used 21 iterations (0.294s) to cluster 8173 items into 250 clusters\n",
      "used 26 iterations (0.911s) to cluster 8173 items into 500 clusters\n",
      "used 19 iterations (0.806s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (0.98s) to cluster 8173 items into 1000 clusters\n",
      "used 76 iterations (7.484s) to cluster 8173 items into 1500 clusters\n",
      "used 100 iterations (13.282s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (16.0s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (18.869s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 44 iterations (0.176s) to cluster 8173 items into 50 clusters\n",
      "used 41 iterations (0.48s) to cluster 8173 items into 100 clusters\n",
      "used 34 iterations (0.458s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (0.649s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (0.622s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (0.867s) to cluster 8173 items into 1000 clusters\n",
      "used 14 iterations (1.326s) to cluster 8173 items into 1500 clusters\n",
      "used 15 iterations (2.01s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (1.494s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (18.742s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 45 iterations (1.397s) to cluster 8173 items into 50 clusters\n",
      "used 32 iterations (1.074s) to cluster 8173 items into 100 clusters\n",
      "used 19 iterations (0.811s) to cluster 8173 items into 250 clusters\n",
      "used 21 iterations (1.453s) to cluster 8173 items into 500 clusters\n",
      "used 13 iterations (1.189s) to cluster 8173 items into 750 clusters\n",
      "used 10 iterations (1.506s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.823s) to cluster 8173 items into 1500 clusters\n",
      "used 11 iterations (2.456s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (2.582s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.751s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 60 iterations (1.812s) to cluster 8173 items into 50 clusters\n",
      "used 40 iterations (1.326s) to cluster 8173 items into 100 clusters\n",
      "used 21 iterations (0.925s) to cluster 8173 items into 250 clusters\n",
      "used 15 iterations (0.998s) to cluster 8173 items into 500 clusters\n",
      "used 12 iterations (1.11s) to cluster 8173 items into 750 clusters\n",
      "used 10 iterations (1.447s) to cluster 8173 items into 1000 clusters\n",
      "used 10 iterations (1.839s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.71s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (2.207s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.807s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (1.049s) to cluster 8173 items into 50 clusters\n",
      "used 50 iterations (1.666s) to cluster 8173 items into 100 clusters\n",
      "used 16 iterations (0.696s) to cluster 8173 items into 250 clusters\n",
      "used 18 iterations (1.275s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.567s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (2.085s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.863s) to cluster 8173 items into 1500 clusters\n",
      "used 11 iterations (2.486s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (2.356s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.243s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 51 iterations (0.674s) to cluster 8173 items into 50 clusters\n",
      "used 41 iterations (0.681s) to cluster 8173 items into 100 clusters\n",
      "used 19 iterations (0.471s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (0.859s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.096s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (1.591s) to cluster 8173 items into 1000 clusters\n",
      "used 9 iterations (0.955s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.678s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.186s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (1.785s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (0.71s) to cluster 8173 items into 50 clusters\n",
      "used 41 iterations (0.966s) to cluster 8173 items into 100 clusters\n",
      "used 31 iterations (1.013s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (1.004s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.344s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.216s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.649s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.213s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.988s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (2.233s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.202s) to cluster 8173 items into 50 clusters\n",
      "used 25 iterations (0.251s) to cluster 8173 items into 100 clusters\n",
      "used 20 iterations (0.358s) to cluster 8173 items into 250 clusters\n",
      "used 22 iterations (0.712s) to cluster 8173 items into 500 clusters\n",
      "used 13 iterations (0.836s) to cluster 8173 items into 750 clusters\n",
      "used 13 iterations (1.02s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.212s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.368s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.339s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (1.379s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 18 iterations (0.019s) to cluster 5010 items into 50 clusters\n",
      "used 20 iterations (0.089s) to cluster 5010 items into 100 clusters\n",
      "used 20 iterations (0.184s) to cluster 5010 items into 250 clusters\n",
      "used 10 iterations (0.281s) to cluster 5010 items into 500 clusters\n",
      "used 14 iterations (0.343s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.336s) to cluster 5010 items into 1000 clusters\n",
      "used 11 iterations (0.765s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (0.8s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.688s) to cluster 5010 items into 2500 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 6 iterations (0.59s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 19 iterations (0.024s) to cluster 5010 items into 50 clusters\n",
      "used 16 iterations (0.073s) to cluster 5010 items into 100 clusters\n",
      "used 16 iterations (0.144s) to cluster 5010 items into 250 clusters\n",
      "used 10 iterations (0.373s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.289s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.493s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.404s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.477s) to cluster 5010 items into 2000 clusters\n",
      "used 7 iterations (0.771s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (0.794s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 15 iterations (0.019s) to cluster 5010 items into 50 clusters\n",
      "used 26 iterations (0.12s) to cluster 5010 items into 100 clusters\n",
      "used 26 iterations (0.236s) to cluster 5010 items into 250 clusters\n",
      "used 17 iterations (0.286s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.302s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.573s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.46s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (0.749s) to cluster 5010 items into 2000 clusters\n",
      "used 100 iterations (9.973s) to cluster 5010 items into 2500 clusters\n",
      "used 8 iterations (1.211s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 27 iterations (0.034s) to cluster 5010 items into 50 clusters\n",
      "used 21 iterations (0.101s) to cluster 5010 items into 100 clusters\n",
      "used 21 iterations (0.2s) to cluster 5010 items into 250 clusters\n",
      "used 17 iterations (0.305s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.432s) to cluster 5010 items into 750 clusters\n",
      "used 12 iterations (0.426s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.734s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.468s) to cluster 5010 items into 2000 clusters\n",
      "used 100 iterations (10.54s) to cluster 5010 items into 2500 clusters\n",
      "used 100 iterations (66.3421s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 27 iterations (0.452s) to cluster 5010 items into 50 clusters\n",
      "used 52 iterations (1.119s) to cluster 5010 items into 100 clusters\n",
      "used 19 iterations (0.535s) to cluster 5010 items into 250 clusters\n",
      "used 19 iterations (0.883s) to cluster 5010 items into 500 clusters\n",
      "used 6 iterations (0.385s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.58s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.635s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.64s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.781s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.726s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.513s) to cluster 5010 items into 50 clusters\n",
      "used 28 iterations (0.587s) to cluster 5010 items into 100 clusters\n",
      "used 15 iterations (0.424s) to cluster 5010 items into 250 clusters\n",
      "used 11 iterations (0.501s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.743s) to cluster 5010 items into 750 clusters\n",
      "used 7 iterations (0.515s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.729s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.629s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.618s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.746s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 55 iterations (0.942s) to cluster 5010 items into 50 clusters\n",
      "used 44 iterations (0.94s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.497s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.695s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (0.672s) to cluster 5010 items into 750 clusters\n",
      "used 17 iterations (1.317s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.96s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.644s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (1.022s) to cluster 5010 items into 2500 clusters\n",
      "used 3 iterations (0.545s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (0.217s) to cluster 5010 items into 50 clusters\n",
      "used 23 iterations (0.256s) to cluster 5010 items into 100 clusters\n",
      "used 22 iterations (0.375s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.392s) to cluster 5010 items into 500 clusters\n",
      "used 18 iterations (0.668s) to cluster 5010 items into 750 clusters\n",
      "used 21 iterations (1.283s) to cluster 5010 items into 1000 clusters\n",
      "used 13 iterations (1.146s) to cluster 5010 items into 1500 clusters\n",
      "used 18 iterations (1.866s) to cluster 5010 items into 2000 clusters\n",
      "used 16 iterations (2.199s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (0.952s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 33 iterations (0.378s) to cluster 5010 items into 50 clusters\n",
      "used 19 iterations (0.277s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.373s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.393s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (0.549s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.493s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.802s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.723s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.513s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.804s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 10 iterations (0.032s) to cluster 5010 items into 50 clusters\n",
      "used 12 iterations (0.102s) to cluster 5010 items into 100 clusters\n",
      "used 14 iterations (0.161s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.283s) to cluster 5010 items into 500 clusters\n",
      "used 14 iterations (0.618s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.346s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.512s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.499s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.659s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.776s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 100 iterations (0.589s) to cluster 8173 items into 50 clusters\n",
      "used 86 iterations (0.601s) to cluster 8173 items into 100 clusters\n",
      "used 43 iterations (0.825s) to cluster 8173 items into 250 clusters\n",
      "used 26 iterations (0.918s) to cluster 8173 items into 500 clusters\n",
      "used 21 iterations (0.876s) to cluster 8173 items into 750 clusters\n",
      "used 16 iterations (1.079s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.235s) to cluster 8173 items into 1500 clusters\n",
      "used 17 iterations (2.029s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (1.698s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (1.48s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 41 iterations (0.166s) to cluster 8173 items into 50 clusters\n",
      "used 53 iterations (0.361s) to cluster 8173 items into 100 clusters\n",
      "used 35 iterations (0.491s) to cluster 8173 items into 250 clusters\n",
      "used 21 iterations (0.783s) to cluster 8173 items into 500 clusters\n",
      "used 20 iterations (0.841s) to cluster 8173 items into 750 clusters\n",
      "used 21 iterations (1.581s) to cluster 8173 items into 1000 clusters\n",
      "used 12 iterations (1.193s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.177s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.275s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (1.489s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 21 iterations (0.089s) to cluster 8173 items into 50 clusters\n",
      "used 35 iterations (0.24s) to cluster 8173 items into 100 clusters\n",
      "used 22 iterations (0.314s) to cluster 8173 items into 250 clusters\n",
      "used 19 iterations (0.669s) to cluster 8173 items into 500 clusters\n",
      "used 25 iterations (1.494s) to cluster 8173 items into 750 clusters\n",
      "used 16 iterations (0.901s) to cluster 8173 items into 1000 clusters\n",
      "used 15 iterations (1.655s) to cluster 8173 items into 1500 clusters\n",
      "used 100 iterations (12.989s) to cluster 8173 items into 2000 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 100 iterations (16.565s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (23.207s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 50 iterations (0.216s) to cluster 8173 items into 50 clusters\n",
      "used 50 iterations (0.384s) to cluster 8173 items into 100 clusters\n",
      "used 31 iterations (0.444s) to cluster 8173 items into 250 clusters\n",
      "used 26 iterations (0.727s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (0.795s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.03s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.122s) to cluster 8173 items into 1500 clusters\n",
      "used 100 iterations (12.362s) to cluster 8173 items into 2000 clusters\n",
      "used 11 iterations (1.917s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (1.695s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 36 iterations (1.049s) to cluster 8173 items into 50 clusters\n",
      "used 39 iterations (1.244s) to cluster 8173 items into 100 clusters\n",
      "used 23 iterations (0.942s) to cluster 8173 items into 250 clusters\n",
      "used 18 iterations (1.18s) to cluster 8173 items into 500 clusters\n",
      "used 16 iterations (1.397s) to cluster 8173 items into 750 clusters\n",
      "used 10 iterations (1.185s) to cluster 8173 items into 1000 clusters\n",
      "used 9 iterations (1.996s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.861s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.911s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.362s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 50 iterations (1.56s) to cluster 8173 items into 50 clusters\n",
      "used 43 iterations (1.441s) to cluster 8173 items into 100 clusters\n",
      "used 27 iterations (1.203s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (1.173s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (1.522s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (2.092s) to cluster 8173 items into 1000 clusters\n",
      "used 12 iterations (2.275s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.659s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.01s) to cluster 8173 items into 2500 clusters\n",
      "used 5 iterations (1.698s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 42 iterations (1.303s) to cluster 8173 items into 50 clusters\n",
      "used 29 iterations (1.002s) to cluster 8173 items into 100 clusters\n",
      "used 34 iterations (1.515s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (1.175s) to cluster 8173 items into 500 clusters\n",
      "used 18 iterations (1.684s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.958s) to cluster 8173 items into 1000 clusters\n",
      "used 9 iterations (1.779s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.716s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (2.745s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.949s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 44 iterations (0.588s) to cluster 8173 items into 50 clusters\n",
      "used 32 iterations (0.524s) to cluster 8173 items into 100 clusters\n",
      "used 24 iterations (0.61s) to cluster 8173 items into 250 clusters\n",
      "used 19 iterations (0.796s) to cluster 8173 items into 500 clusters\n",
      "used 12 iterations (0.69s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.145s) to cluster 8173 items into 1000 clusters\n",
      "used 19 iterations (2.57s) to cluster 8173 items into 1500 clusters\n",
      "used 12 iterations (1.92s) to cluster 8173 items into 2000 clusters\n",
      "used 11 iterations (2.347s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (1.596s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 27 iterations (0.569s) to cluster 8173 items into 50 clusters\n",
      "used 33 iterations (0.782s) to cluster 8173 items into 100 clusters\n",
      "used 23 iterations (0.744s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (0.877s) to cluster 8173 items into 500 clusters\n",
      "used 11 iterations (0.857s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.321s) to cluster 8173 items into 1000 clusters\n",
      "used 14 iterations (2.189s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.488s) to cluster 8173 items into 2000 clusters\n",
      "used 6 iterations (1.598s) to cluster 8173 items into 2500 clusters\n",
      "used 5 iterations (1.099s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 36 iterations (0.255s) to cluster 8173 items into 50 clusters\n",
      "used 23 iterations (0.226s) to cluster 8173 items into 100 clusters\n",
      "used 29 iterations (0.529s) to cluster 8173 items into 250 clusters\n",
      "used 19 iterations (0.624s) to cluster 8173 items into 500 clusters\n",
      "used 19 iterations (1.037s) to cluster 8173 items into 750 clusters\n",
      "used 16 iterations (1.087s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (1.412s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.591s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.136s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (1.794s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 23 iterations (0.026s) to cluster 5010 items into 50 clusters\n",
      "used 14 iterations (0.065s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.155s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.218s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.226s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.305s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.414s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.467s) to cluster 5010 items into 2000 clusters\n",
      "used 11 iterations (1.331s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.5s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 20 iterations (0.024s) to cluster 5010 items into 50 clusters\n",
      "used 19 iterations (0.084s) to cluster 5010 items into 100 clusters\n",
      "used 23 iterations (0.424s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.219s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (0.326s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.293s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.394s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.464s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.679s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.498s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (0.04s) to cluster 5010 items into 50 clusters\n",
      "used 23 iterations (0.101s) to cluster 5010 items into 100 clusters\n",
      "used 15 iterations (0.136s) to cluster 5010 items into 250 clusters\n",
      "used 16 iterations (0.274s) to cluster 5010 items into 500 clusters\n",
      "used 16 iterations (0.597s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.368s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.719s) to cluster 5010 items into 1500 clusters\n",
      "used 100 iterations (7.933s) to cluster 5010 items into 2000 clusters\n",
      "used 9 iterations (0.752s) to cluster 5010 items into 2500 clusters\n",
      "used 13 iterations (1.7s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (0.035s) to cluster 5010 items into 50 clusters\n",
      "used 19 iterations (0.087s) to cluster 5010 items into 100 clusters\n",
      "used 19 iterations (0.17s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.246s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.254s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.535s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.411s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (0.74s) to cluster 5010 items into 2000 clusters\n",
      "used 17 iterations (1.656s) to cluster 5010 items into 2500 clusters\n",
      "used 100 iterations (11.632s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.489s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.53s) to cluster 5010 items into 100 clusters\n",
      "used 11 iterations (0.321s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.596s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.552s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.748s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.71s) to cluster 5010 items into 1500 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 8 iterations (1.24s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.946s) to cluster 5010 items into 2500 clusters\n",
      "used 3 iterations (0.738s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (0.528s) to cluster 5010 items into 50 clusters\n",
      "used 33 iterations (0.669s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.505s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.576s) to cluster 5010 items into 500 clusters\n",
      "used 7 iterations (0.44s) to cluster 5010 items into 750 clusters\n",
      "used 10 iterations (0.712s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.925s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.95s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.834s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.908s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 28 iterations (0.45s) to cluster 5010 items into 50 clusters\n",
      "used 21 iterations (0.444s) to cluster 5010 items into 100 clusters\n",
      "used 24 iterations (0.692s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.549s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.613s) to cluster 5010 items into 750 clusters\n",
      "used 13 iterations (0.979s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.933s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (1.109s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.98s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.9s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 31 iterations (0.216s) to cluster 5010 items into 50 clusters\n",
      "used 38 iterations (0.405s) to cluster 5010 items into 100 clusters\n",
      "used 27 iterations (0.453s) to cluster 5010 items into 250 clusters\n",
      "used 21 iterations (0.543s) to cluster 5010 items into 500 clusters\n",
      "used 16 iterations (0.594s) to cluster 5010 items into 750 clusters\n",
      "used 14 iterations (0.883s) to cluster 5010 items into 1000 clusters\n",
      "used 11 iterations (0.987s) to cluster 5010 items into 1500 clusters\n",
      "used 10 iterations (1.101s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.658s) to cluster 5010 items into 2500 clusters\n",
      "used 8 iterations (1.247s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 24 iterations (0.243s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.386s) to cluster 5010 items into 100 clusters\n",
      "used 13 iterations (0.281s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.364s) to cluster 5010 items into 500 clusters\n",
      "used 16 iterations (0.775s) to cluster 5010 items into 750 clusters\n",
      "used 7 iterations (0.448s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.725s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.628s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.524s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.618s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 23 iterations (0.075s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.167s) to cluster 5010 items into 100 clusters\n",
      "used 12 iterations (0.141s) to cluster 5010 items into 250 clusters\n",
      "used 9 iterations (0.176s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.259s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.289s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.462s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.364s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.651s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.68s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 100 iterations (0.604s) to cluster 8173 items into 50 clusters\n",
      "used 92 iterations (0.623s) to cluster 8173 items into 100 clusters\n",
      "used 32 iterations (0.653s) to cluster 8173 items into 250 clusters\n",
      "used 38 iterations (1.231s) to cluster 8173 items into 500 clusters\n",
      "used 19 iterations (0.795s) to cluster 8173 items into 750 clusters\n",
      "used 20 iterations (1.532s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (1.278s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.067s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.248s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.056s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 60 iterations (0.242s) to cluster 8173 items into 50 clusters\n",
      "used 64 iterations (0.633s) to cluster 8173 items into 100 clusters\n",
      "used 49 iterations (0.687s) to cluster 8173 items into 250 clusters\n",
      "used 32 iterations (0.867s) to cluster 8173 items into 500 clusters\n",
      "used 31 iterations (1.733s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (0.834s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.059s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.436s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (1.403s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (1.307s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.122s) to cluster 8173 items into 50 clusters\n",
      "used 19 iterations (0.342s) to cluster 8173 items into 100 clusters\n",
      "used 30 iterations (0.434s) to cluster 8173 items into 250 clusters\n",
      "used 19 iterations (0.727s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (0.785s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (0.772s) to cluster 8173 items into 1000 clusters\n",
      "used 30 iterations (2.873s) to cluster 8173 items into 1500 clusters\n",
      "used 15 iterations (2.097s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (16.0004s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (19.262s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 38 iterations (0.371s) to cluster 8173 items into 50 clusters\n",
      "used 50 iterations (0.331s) to cluster 8173 items into 100 clusters\n",
      "used 32 iterations (0.44s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (0.76s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (0.623s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (0.876s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.083s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.248s) to cluster 8173 items into 2000 clusters\n",
      "used 9 iterations (1.54s) to cluster 8173 items into 2500 clusters\n",
      "used 11 iterations (3.314s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 49 iterations (1.471s) to cluster 8173 items into 50 clusters\n",
      "used 26 iterations (0.88s) to cluster 8173 items into 100 clusters\n",
      "used 31 iterations (1.387s) to cluster 8173 items into 250 clusters\n",
      "used 16 iterations (1.101s) to cluster 8173 items into 500 clusters\n",
      "used 15 iterations (1.41s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.58s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (2.108s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.51s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (2.018s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.055s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 42 iterations (1.282s) to cluster 8173 items into 50 clusters\n",
      "used 38 iterations (1.299s) to cluster 8173 items into 100 clusters\n",
      "used 19 iterations (0.83s) to cluster 8173 items into 250 clusters\n",
      "used 15 iterations (1.031s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (1.308s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.741s) to cluster 8173 items into 1000 clusters\n",
      "used 8 iterations (1.441s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.336s) to cluster 8173 items into 2000 clusters\n",
      "used 6 iterations (1.75s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.934s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 35 iterations (1.073s) to cluster 8173 items into 50 clusters\n",
      "used 35 iterations (1.199s) to cluster 8173 items into 100 clusters\n",
      "used 34 iterations (1.479s) to cluster 8173 items into 250 clusters\n",
      "used 17 iterations (1.147s) to cluster 8173 items into 500 clusters\n",
      "used 13 iterations (1.229s) to cluster 8173 items into 750 clusters\n",
      "used 19 iterations (2.756s) to cluster 8173 items into 1000 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 10 iterations (1.769s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (2.38s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (2.059s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.067s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 54 iterations (0.717s) to cluster 8173 items into 50 clusters\n",
      "used 33 iterations (0.544s) to cluster 8173 items into 100 clusters\n",
      "used 23 iterations (0.573s) to cluster 8173 items into 250 clusters\n",
      "used 24 iterations (1.019s) to cluster 8173 items into 500 clusters\n",
      "used 13 iterations (0.983s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.096s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.425s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.302s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.816s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (1.585s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 45 iterations (0.929s) to cluster 8173 items into 50 clusters\n",
      "used 27 iterations (0.623s) to cluster 8173 items into 100 clusters\n",
      "used 28 iterations (0.976s) to cluster 8173 items into 250 clusters\n",
      "used 13 iterations (0.662s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (1.092s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.492s) to cluster 8173 items into 1000 clusters\n",
      "used 9 iterations (1.15s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.695s) to cluster 8173 items into 2000 clusters\n",
      "used 6 iterations (1.243s) to cluster 8173 items into 2500 clusters\n",
      "used 4 iterations (1.107s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 20 iterations (0.145s) to cluster 8173 items into 50 clusters\n",
      "used 39 iterations (0.388s) to cluster 8173 items into 100 clusters\n",
      "used 28 iterations (0.49s) to cluster 8173 items into 250 clusters\n",
      "used 19 iterations (0.622s) to cluster 8173 items into 500 clusters\n",
      "used 28 iterations (1.703s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (0.884s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.155s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.119s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.453s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.223s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 25 iterations (0.033s) to cluster 5010 items into 50 clusters\n",
      "used 24 iterations (0.112s) to cluster 5010 items into 100 clusters\n",
      "used 15 iterations (0.141s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.211s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (0.384s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.303s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.706s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (0.727s) to cluster 5010 items into 2000 clusters\n",
      "used 7 iterations (0.776s) to cluster 5010 items into 2500 clusters\n",
      "used 7 iterations (0.688s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 25 iterations (0.032s) to cluster 5010 items into 50 clusters\n",
      "used 33 iterations (0.153s) to cluster 5010 items into 100 clusters\n",
      "used 18 iterations (0.164s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.213s) to cluster 5010 items into 500 clusters\n",
      "used 7 iterations (0.172s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.472s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.503s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.391s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.71s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (0.582s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 23 iterations (0.03s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.112s) to cluster 5010 items into 100 clusters\n",
      "used 17 iterations (0.161s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.207s) to cluster 5010 items into 500 clusters\n",
      "used 16 iterations (0.394s) to cluster 5010 items into 750 clusters\n",
      "used 13 iterations (0.438s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.708s) to cluster 5010 items into 1500 clusters\n",
      "used 100 iterations (8.065s) to cluster 5010 items into 2000 clusters\n",
      "used 8 iterations (0.762s) to cluster 5010 items into 2500 clusters\n",
      "used 8 iterations (0.996s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 30 iterations (0.042s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.121s) to cluster 5010 items into 100 clusters\n",
      "used 29 iterations (0.471s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.243s) to cluster 5010 items into 500 clusters\n",
      "used 16 iterations (0.408s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.48s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.455s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (0.75s) to cluster 5010 items into 2000 clusters\n",
      "used 9 iterations (0.945s) to cluster 5010 items into 2500 clusters\n",
      "used 100 iterations (11.6481s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 24 iterations (0.414s) to cluster 5010 items into 50 clusters\n",
      "used 42 iterations (0.899s) to cluster 5010 items into 100 clusters\n",
      "used 13 iterations (0.376s) to cluster 5010 items into 250 clusters\n",
      "used 11 iterations (0.515s) to cluster 5010 items into 500 clusters\n",
      "used 8 iterations (0.512s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.687s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.608s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.632s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.79s) to cluster 5010 items into 2500 clusters\n",
      "used 3 iterations (0.505s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 20 iterations (0.347s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.534s) to cluster 5010 items into 100 clusters\n",
      "used 13 iterations (0.358s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.551s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.718s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.603s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.599s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.773s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.815s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.702s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 29 iterations (0.498s) to cluster 5010 items into 50 clusters\n",
      "used 26 iterations (0.54s) to cluster 5010 items into 100 clusters\n",
      "used 25 iterations (0.697s) to cluster 5010 items into 250 clusters\n",
      "used 12 iterations (0.566s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.753s) to cluster 5010 items into 750 clusters\n",
      "used 8 iterations (0.826s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.719s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.853s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (1.086s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.703s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 44 iterations (0.313s) to cluster 5010 items into 50 clusters\n",
      "used 21 iterations (0.223s) to cluster 5010 items into 100 clusters\n",
      "used 30 iterations (0.5s) to cluster 5010 items into 250 clusters\n",
      "used 20 iterations (0.518s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (0.46s) to cluster 5010 items into 750 clusters\n",
      "used 24 iterations (1.401s) to cluster 5010 items into 1000 clusters\n",
      "used 17 iterations (1.435s) to cluster 5010 items into 1500 clusters\n",
      "used 11 iterations (1.183s) to cluster 5010 items into 2000 clusters\n",
      "used 15 iterations (2.099s) to cluster 5010 items into 2500 clusters\n",
      "used 9 iterations (1.238s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 27 iterations (0.302s) to cluster 5010 items into 50 clusters\n",
      "used 25 iterations (0.376s) to cluster 5010 items into 100 clusters\n",
      "used 15 iterations (0.324s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.477s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (0.548s) to cluster 5010 items into 750 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 10 iterations (0.622s) to cluster 5010 items into 1000 clusters\n",
      "used 5 iterations (0.451s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.853s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.676s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.774s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 16 iterations (0.049s) to cluster 5010 items into 50 clusters\n",
      "used 11 iterations (0.073s) to cluster 5010 items into 100 clusters\n",
      "used 23 iterations (0.268s) to cluster 5010 items into 250 clusters\n",
      "used 9 iterations (0.188s) to cluster 5010 items into 500 clusters\n",
      "used 11 iterations (0.317s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.416s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.521s) to cluster 5010 items into 1500 clusters\n",
      "used 6 iterations (0.84s) to cluster 5010 items into 2000 clusters\n",
      "used 6 iterations (0.544s) to cluster 5010 items into 2500 clusters\n",
      "used 7 iterations (0.979s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 79 iterations (0.32s) to cluster 8173 items into 50 clusters\n",
      "used 100 iterations (0.878s) to cluster 8173 items into 100 clusters\n",
      "used 41 iterations (0.785s) to cluster 8173 items into 250 clusters\n",
      "used 22 iterations (0.604s) to cluster 8173 items into 500 clusters\n",
      "used 19 iterations (1.002s) to cluster 8173 items into 750 clusters\n",
      "used 26 iterations (1.846s) to cluster 8173 items into 1000 clusters\n",
      "used 13 iterations (1.065s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.504s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.032s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (1.644s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 55 iterations (0.44s) to cluster 8173 items into 50 clusters\n",
      "used 85 iterations (0.579s) to cluster 8173 items into 100 clusters\n",
      "used 32 iterations (0.442s) to cluster 8173 items into 250 clusters\n",
      "used 22 iterations (0.812s) to cluster 8173 items into 500 clusters\n",
      "used 28 iterations (1.388s) to cluster 8173 items into 750 clusters\n",
      "used 15 iterations (1.046s) to cluster 8173 items into 1000 clusters\n",
      "used 14 iterations (1.353s) to cluster 8173 items into 1500 clusters\n",
      "used 9 iterations (1.186s) to cluster 8173 items into 2000 clusters\n",
      "used 13 iterations (2.227s) to cluster 8173 items into 2500 clusters\n",
      "used 9 iterations (1.617s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 39 iterations (0.157s) to cluster 8173 items into 50 clusters\n",
      "used 29 iterations (0.193s) to cluster 8173 items into 100 clusters\n",
      "used 41 iterations (0.781s) to cluster 8173 items into 250 clusters\n",
      "used 22 iterations (0.609s) to cluster 8173 items into 500 clusters\n",
      "used 19 iterations (0.871s) to cluster 8173 items into 750 clusters\n",
      "used 17 iterations (1.157s) to cluster 8173 items into 1000 clusters\n",
      "used 22 iterations (2.222s) to cluster 8173 items into 1500 clusters\n",
      "used 70 iterations (9.0s) to cluster 8173 items into 2000 clusters\n",
      "used 100 iterations (16.2131s) to cluster 8173 items into 2500 clusters\n",
      "used 100 iterations (18.9581s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 91 iterations (0.391s) to cluster 8173 items into 50 clusters\n",
      "used 53 iterations (0.352s) to cluster 8173 items into 100 clusters\n",
      "used 23 iterations (0.539s) to cluster 8173 items into 250 clusters\n",
      "used 20 iterations (0.543s) to cluster 8173 items into 500 clusters\n",
      "used 21 iterations (1.104s) to cluster 8173 items into 750 clusters\n",
      "used 14 iterations (1.214s) to cluster 8173 items into 1000 clusters\n",
      "used 100 iterations (9.637s) to cluster 8173 items into 1500 clusters\n",
      "used 11 iterations (1.351s) to cluster 8173 items into 2000 clusters\n",
      "used 11 iterations (1.716s) to cluster 8173 items into 2500 clusters\n",
      "used 8 iterations (1.436s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 46 iterations (1.407s) to cluster 8173 items into 50 clusters\n",
      "used 37 iterations (1.262s) to cluster 8173 items into 100 clusters\n",
      "used 20 iterations (0.882s) to cluster 8173 items into 250 clusters\n",
      "used 18 iterations (1.257s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (1.527s) to cluster 8173 items into 750 clusters\n",
      "used 9 iterations (1.196s) to cluster 8173 items into 1000 clusters\n",
      "used 19 iterations (3.322s) to cluster 8173 items into 1500 clusters\n",
      "used 8 iterations (1.792s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.79s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.932s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 52 iterations (1.633s) to cluster 8173 items into 50 clusters\n",
      "used 23 iterations (0.778s) to cluster 8173 items into 100 clusters\n",
      "used 22 iterations (0.987s) to cluster 8173 items into 250 clusters\n",
      "used 16 iterations (1.137s) to cluster 8173 items into 500 clusters\n",
      "used 17 iterations (1.6s) to cluster 8173 items into 750 clusters\n",
      "used 13 iterations (1.896s) to cluster 8173 items into 1000 clusters\n",
      "used 9 iterations (1.494s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (2.365s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (2.259s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.748s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 65 iterations (1.963s) to cluster 8173 items into 50 clusters\n",
      "used 36 iterations (1.193s) to cluster 8173 items into 100 clusters\n",
      "used 32 iterations (1.432s) to cluster 8173 items into 250 clusters\n",
      "used 16 iterations (1.099s) to cluster 8173 items into 500 clusters\n",
      "used 18 iterations (1.798s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.576s) to cluster 8173 items into 1000 clusters\n",
      "used 12 iterations (2.239s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.576s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.851s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (2.22s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 38 iterations (0.469s) to cluster 8173 items into 50 clusters\n",
      "used 62 iterations (1.007s) to cluster 8173 items into 100 clusters\n",
      "used 24 iterations (0.599s) to cluster 8173 items into 250 clusters\n",
      "used 24 iterations (0.992s) to cluster 8173 items into 500 clusters\n",
      "used 19 iterations (1.344s) to cluster 8173 items into 750 clusters\n",
      "used 12 iterations (1.167s) to cluster 8173 items into 1000 clusters\n",
      "used 11 iterations (1.403s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.16s) to cluster 8173 items into 2000 clusters\n",
      "used 10 iterations (2.117s) to cluster 8173 items into 2500 clusters\n",
      "used 7 iterations (1.633s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 26 iterations (0.531s) to cluster 8173 items into 50 clusters\n",
      "used 41 iterations (0.996s) to cluster 8173 items into 100 clusters\n",
      "used 24 iterations (0.779s) to cluster 8173 items into 250 clusters\n",
      "used 24 iterations (1.263s) to cluster 8173 items into 500 clusters\n",
      "used 11 iterations (0.849s) to cluster 8173 items into 750 clusters\n",
      "used 11 iterations (1.222s) to cluster 8173 items into 1000 clusters\n",
      "used 8 iterations (1.247s) to cluster 8173 items into 1500 clusters\n",
      "used 7 iterations (1.353s) to cluster 8173 items into 2000 clusters\n",
      "used 7 iterations (1.806s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.654s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 33 iterations (0.256s) to cluster 8173 items into 50 clusters\n",
      "used 46 iterations (0.466s) to cluster 8173 items into 100 clusters\n",
      "used 23 iterations (0.417s) to cluster 8173 items into 250 clusters\n",
      "used 27 iterations (0.881s) to cluster 8173 items into 500 clusters\n",
      "used 14 iterations (0.89s) to cluster 8173 items into 750 clusters\n",
      "used 17 iterations (1.294s) to cluster 8173 items into 1000 clusters\n",
      "used 12 iterations (1.182s) to cluster 8173 items into 1500 clusters\n",
      "used 10 iterations (1.318s) to cluster 8173 items into 2000 clusters\n",
      "used 8 iterations (1.328s) to cluster 8173 items into 2500 clusters\n",
      "used 6 iterations (1.43s) to cluster 8173 items into 3000 clusters\n",
      "Completed.\n",
      "used 26 iterations (0.036s) to cluster 5010 items into 50 clusters\n",
      "used 22 iterations (0.102s) to cluster 5010 items into 100 clusters\n",
      "used 12 iterations (0.111s) to cluster 5010 items into 250 clusters\n",
      "used 14 iterations (0.234s) to cluster 5010 items into 500 clusters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "used 15 iterations (0.515s) to cluster 5010 items into 750 clusters\n",
      "used 14 iterations (0.464s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.45s) to cluster 5010 items into 1500 clusters\n",
      "used 9 iterations (0.818s) to cluster 5010 items into 2000 clusters\n",
      "used 7 iterations (0.576s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (0.573s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 20 iterations (0.026s) to cluster 5010 items into 50 clusters\n",
      "used 16 iterations (0.068s) to cluster 5010 items into 100 clusters\n",
      "used 12 iterations (0.103s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.248s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.248s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.302s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (0.414s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.729s) to cluster 5010 items into 2000 clusters\n",
      "used 7 iterations (0.761s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.484s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 27 iterations (0.028s) to cluster 5010 items into 50 clusters\n",
      "used 27 iterations (0.126s) to cluster 5010 items into 100 clusters\n",
      "used 16 iterations (0.143s) to cluster 5010 items into 250 clusters\n",
      "used 21 iterations (0.567s) to cluster 5010 items into 500 clusters\n",
      "used 16 iterations (0.394s) to cluster 5010 items into 750 clusters\n",
      "used 16 iterations (0.746s) to cluster 5010 items into 1000 clusters\n",
      "used 9 iterations (0.462s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (0.664s) to cluster 5010 items into 2000 clusters\n",
      "used 10 iterations (0.833s) to cluster 5010 items into 2500 clusters\n",
      "used 7 iterations (0.779s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 39 iterations (0.05s) to cluster 5010 items into 50 clusters\n",
      "used 22 iterations (0.095s) to cluster 5010 items into 100 clusters\n",
      "used 19 iterations (0.396s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.246s) to cluster 5010 items into 500 clusters\n",
      "used 12 iterations (0.309s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.3s) to cluster 5010 items into 1000 clusters\n",
      "used 11 iterations (0.608s) to cluster 5010 items into 1500 clusters\n",
      "used 8 iterations (0.741s) to cluster 5010 items into 2000 clusters\n",
      "used 100 iterations (10.036s) to cluster 5010 items into 2500 clusters\n",
      "used 11 iterations (1.116s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 34 iterations (0.573s) to cluster 5010 items into 50 clusters\n",
      "used 17 iterations (0.358s) to cluster 5010 items into 100 clusters\n",
      "used 20 iterations (0.569s) to cluster 5010 items into 250 clusters\n",
      "used 15 iterations (0.68s) to cluster 5010 items into 500 clusters\n",
      "used 8 iterations (0.484s) to cluster 5010 items into 750 clusters\n",
      "used 7 iterations (0.536s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.71s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.641s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (1.031s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.684s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 42 iterations (0.704s) to cluster 5010 items into 50 clusters\n",
      "used 23 iterations (0.48s) to cluster 5010 items into 100 clusters\n",
      "used 16 iterations (0.454s) to cluster 5010 items into 250 clusters\n",
      "used 17 iterations (0.774s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.533s) to cluster 5010 items into 750 clusters\n",
      "used 11 iterations (0.812s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (1.015s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.635s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.788s) to cluster 5010 items into 2500 clusters\n",
      "used 5 iterations (0.903s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 29 iterations (0.505s) to cluster 5010 items into 50 clusters\n",
      "used 23 iterations (0.488s) to cluster 5010 items into 100 clusters\n",
      "used 27 iterations (0.757s) to cluster 5010 items into 250 clusters\n",
      "used 13 iterations (0.586s) to cluster 5010 items into 500 clusters\n",
      "used 14 iterations (0.864s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.656s) to cluster 5010 items into 1000 clusters\n",
      "used 8 iterations (1.023s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.64s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.845s) to cluster 5010 items into 2500 clusters\n",
      "used 3 iterations (0.537s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 46 iterations (0.311s) to cluster 5010 items into 50 clusters\n",
      "used 26 iterations (0.278s) to cluster 5010 items into 100 clusters\n",
      "used 30 iterations (0.503s) to cluster 5010 items into 250 clusters\n",
      "used 20 iterations (0.518s) to cluster 5010 items into 500 clusters\n",
      "used 13 iterations (0.483s) to cluster 5010 items into 750 clusters\n",
      "used 16 iterations (0.998s) to cluster 5010 items into 1000 clusters\n",
      "used 10 iterations (0.91s) to cluster 5010 items into 1500 clusters\n",
      "used 11 iterations (1.188s) to cluster 5010 items into 2000 clusters\n",
      "used 11 iterations (1.419s) to cluster 5010 items into 2500 clusters\n",
      "used 7 iterations (1.138s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 25 iterations (0.266s) to cluster 5010 items into 50 clusters\n",
      "used 35 iterations (0.505s) to cluster 5010 items into 100 clusters\n",
      "used 27 iterations (0.566s) to cluster 5010 items into 250 clusters\n",
      "used 10 iterations (0.316s) to cluster 5010 items into 500 clusters\n",
      "used 10 iterations (0.493s) to cluster 5010 items into 750 clusters\n",
      "used 9 iterations (0.537s) to cluster 5010 items into 1000 clusters\n",
      "used 6 iterations (0.723s) to cluster 5010 items into 1500 clusters\n",
      "used 7 iterations (0.746s) to cluster 5010 items into 2000 clusters\n",
      "used 4 iterations (0.692s) to cluster 5010 items into 2500 clusters\n",
      "used 6 iterations (1.195s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n",
      "used 22 iterations (0.07s) to cluster 5010 items into 50 clusters\n",
      "used 14 iterations (0.1s) to cluster 5010 items into 100 clusters\n",
      "used 15 iterations (0.181s) to cluster 5010 items into 250 clusters\n",
      "used 11 iterations (0.224s) to cluster 5010 items into 500 clusters\n",
      "used 9 iterations (0.264s) to cluster 5010 items into 750 clusters\n",
      "used 12 iterations (0.566s) to cluster 5010 items into 1000 clusters\n",
      "used 7 iterations (0.581s) to cluster 5010 items into 1500 clusters\n",
      "used 5 iterations (0.363s) to cluster 5010 items into 2000 clusters\n",
      "used 5 iterations (0.442s) to cluster 5010 items into 2500 clusters\n",
      "used 4 iterations (0.53s) to cluster 5010 items into 3000 clusters\n",
      "Completed.\n"
     ]
    }
   ],
   "source": [
    "for h in range(len(eo_testset_list)):\n",
    "    for i in range(len(dataset_names)):\n",
    "      for j in range(len(embed_types)):\n",
    "        indices_list = []\n",
    "        data = pd.read_csv(\"data/output/\" +dataset_names[i] + '_' + embed_types[j] + '_full.csv', index_col=0)\n",
    "        if dataset_names[i]==\"eo\":\n",
    "            idx = Diff(range(1, max_obs_eo), eo_testset_list[h])\n",
    "        elif dataset_names[i] == \"stwts\":\n",
    "            idx = Diff(range(1, max_obs_stwts), stwts_testset_list[h])\n",
    "        else:\n",
    "            print(\"Error\")\n",
    "        data = data.iloc[idx]\n",
    "        data = data.to_numpy()\n",
    "        data = si.torch.from_numpy(data).float()\n",
    "        for c in counts:\n",
    "          indices_list.append(si.kmeans_indices(data, c))\n",
    "        with open(\"data/output/\" +'indices_'+dataset_names[i]+'_'+embed_types[j]+'_kmeans_iter' + str(h+1) + '.txt', 'w') as filehandle:\n",
    "          filehandle.writelines(\"%s\\n\" % idl for idl in indices_list)\n",
    "        print('Completed.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "W_CTEKNDivOy"
   },
   "source": [
    "## Greedy farthest points based on KL Divergence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 2818914,
     "status": "ok",
     "timestamp": 1616741158067,
     "user": {
      "displayName": "Apurva Bhargava",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi3hHA-32IVQPOzXK40Itcc5oZmMDf0Vsnw_e_afg=s64",
      "userId": "07288249218888651888"
     },
     "user_tz": 240
    },
    "id": "nttsO8vDi0G0",
    "outputId": "0a6897e2-6325-4d68-91e2-ec76efaded7e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
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      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    }
   ],
   "source": [
    "for h in range(len(eo_testset_list)):\n",
    "    for i in range(len(dataset_names)):\n",
    "      for j in range(len(embed_types)):\n",
    "        if dataset_names[i]==\"eo\":\n",
    "            idx = Diff(range(1, max_obs_eo), eo_testset_list[h])\n",
    "        elif dataset_names[i] == \"stwts\":\n",
    "            idx = Diff(range(1, max_obs_stwts), stwts_testset_list[h])\n",
    "        else:\n",
    "            print(\"Error\")      \n",
    "        kld_matrix = np.load(\"data/output/\" +dataset_names[i] + '_kld_' + embed_types[j] + '.npy')\n",
    "        kld_matrix = kld_matrix[idx,:]\n",
    "        kld_matrix = kld_matrix[:,idx]\n",
    "        #print(kld_matrix.shape)\n",
    "        indices_list = list(si.farthestPointSampler(kld_matrix, max(counts)))\n",
    "        with open(\"data/output/\" +'indices_'+dataset_names[i]+'_'+embed_types[j]+'_kld_iter' + str(h+1) + '.txt', 'w') as filehandle:\n",
    "          filehandle.writelines(\"%s\" % indices_list)\n",
    "        print('Completed.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TGB2wJ8x1whV"
   },
   "source": [
    "## Greedy Farthest points based on Kolmogorov-Smirnov measure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 2695703,
     "status": "ok",
     "timestamp": 1616744770203,
     "user": {
      "displayName": "Apurva Bhargava",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi3hHA-32IVQPOzXK40Itcc5oZmMDf0Vsnw_e_afg=s64",
      "userId": "07288249218888651888"
     },
     "user_tz": 240
    },
    "id": "fSYAD9gX1pwb",
    "outputId": "e1ad8ea3-0fe8-427e-b6e2-137d55460ba4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
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      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    }
   ],
   "source": [
    "for h in range(len(eo_testset_list)):\n",
    "    for i in range(len(dataset_names)):\n",
    "      for j in range(len(embed_types)):\n",
    "        if dataset_names[i]==\"eo\":\n",
    "            idx = Diff(range(1, max_obs_eo), eo_testset_list[h])\n",
    "        elif dataset_names[i] == \"stwts\":\n",
    "            idx = Diff(range(1, max_obs_stwts), stwts_testset_list[h])\n",
    "        else:\n",
    "            print(\"Error\")      \n",
    "        ks_matrix = np.load(\"data/output/\" +dataset_names[i] + '_ks_' + embed_types[j] + '.npy')\n",
    "        ks_matrix = ks_matrix[idx,:]\n",
    "        ks_matrix = ks_matrix[:,idx]\n",
    "        #print(ks_matrix.shape)\n",
    "        indices_list = list(si.farthestPointSampler(ks_matrix, max(counts)))\n",
    "        with open(\"data/output/\" +'indices_'+dataset_names[i]+'_'+embed_types[j]+'_ks_iter' + str(h+1) + '.txt', 'w') as filehandle:\n",
    "          filehandle.writelines(\"%s\" % indices_list)\n",
    "        print('Completed.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jVxcbiHt1xpn"
   },
   "source": [
    "## Greedy Farthest points based on Cosine Distance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 2451016,
     "status": "ok",
     "timestamp": 1616748121988,
     "user": {
      "displayName": "Apurva Bhargava",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14Gi3hHA-32IVQPOzXK40Itcc5oZmMDf0Vsnw_e_afg=s64",
      "userId": "07288249218888651888"
     },
     "user_tz": 240
    },
    "id": "ibEUHHdW1p31",
    "outputId": "221eb40b-8a25-4c9a-a554-0f7768dedea7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
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      "Completed.\n",
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      "Completed.\n",
      "Completed.\n",
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      "Completed.\n",
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      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    }
   ],
   "source": [
    "for h in range(len(eo_testset_list)):\n",
    "    for i in range(len(dataset_names)):\n",
    "      for j in range(len(embed_types)):\n",
    "        if dataset_names[i]==\"eo\":\n",
    "            idx = Diff(range(1, max_obs_eo), eo_testset_list[h])\n",
    "        elif dataset_names[i] == \"stwts\":\n",
    "            idx = Diff(range(1, max_obs_stwts), stwts_testset_list[h])\n",
    "        else:\n",
    "            print(\"Error\")      \n",
    "        cos_matrix = np.load(\"data/output/\" +dataset_names[i] + '_cos_' + embed_types[j] + '.npy')\n",
    "        cos_matrix = cos_matrix[idx,:]\n",
    "        cos_matrix = cos_matrix[:,idx]\n",
    "        #print(cos_matrix.shape)\n",
    "        indices_list = list(si.farthestPointSampler(cos_matrix, max(counts)))\n",
    "        with open(\"data/output/\" +'indices_'+dataset_names[i]+'_'+embed_types[j]+'_cos_iter' + str(h+1) + '.txt', 'w') as filehandle:\n",
    "          filehandle.writelines(\"%s\" % indices_list)\n",
    "        print('Completed.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## D-Optimality (Taddy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<string>:8: RuntimeWarning: invalid value encountered in matmul\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n",
      "Completed.\n"
     ]
    }
   ],
   "source": [
    "for h in range(len(eo_testset_list)):\n",
    "    for i in range(len(dataset_names)):\n",
    "      for j in range(len(embed_types)):\n",
    "        indices_list = []\n",
    "        data = pd.read_csv(\"data/output/\" +dataset_names[i] + '_' + embed_types[j] + '_full.csv', index_col=0)\n",
    "        if dataset_names[i]==\"eo\":\n",
    "            idx = Diff(range(1, max_obs_eo), eo_testset_list[h])\n",
    "        elif dataset_names[i] == \"stwts\":\n",
    "            idx = Diff(range(1, max_obs_stwts), stwts_testset_list[h])\n",
    "        else:\n",
    "            print(\"Error\")\n",
    "        data = data.iloc[idx]\n",
    "        data = data.to_numpy()\n",
    "        data = si.torch.from_numpy(data).float()\n",
    "        for c in counts:\n",
    "          indices_list.append(si.dopt(data, c))\n",
    "        with open(\"data/output/\" +'indices_'+dataset_names[i]+'_'+embed_types[j]+'_dopt_iter' + str(h+1) + '.txt', 'w') as filehandle:\n",
    "          filehandle.writelines(\"%s\\n\" % idl for idl in indices_list)\n",
    "        print('Completed.')"
   ]
  }
 ],
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